Three flagship AI models shipped within five weeks of each other this spring, and each one briefly held the “best in the world” title before the next one took it. GPT-5.5 launched April 23, 2026, and topped the Artificial Analysis Intelligence Index within a day. Gemini 3.5 Flash arrived May 19 at Google I/O, undercutting both rivals on price while reportedly beating Google’s own larger Gemini 3.1 Pro on coding tasks. Then Claude Opus 4.8 landed May 28, retaking the top benchmark spot at 61.4 on the same index.
For developers choosing an API and everyday users choosing a chat app, that leapfrogging matters less than the underlying numbers: what each model actually costs per million tokens, how each scores on SWE-bench, and where each one is actually available today. This comparison lines up Claude Opus 4.8, GPT-5.5, and Gemini 3.5 Flash on pricing, context windows, benchmark results, and deployment options, pulling specs directly from Anthropic, OpenAI, and Google’s own documentation wherever possible.
The short version: GPT-5.5’s output pricing runs $21 higher per million tokens than Gemini 3.5 Flash ($30 versus $9), Claude Opus 4.8 sits in between at $25, and all three vendors claim frontier-level coding performance. The differences that actually decide which model fits your workload show up in context handling, tool-use behavior, and deployment surface, not just the headline benchmark score.
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Claude Opus 4.8 vs GPT-5.5 vs Gemini 3.5 Flash: Full Specs Comparison
Before the narrative, here is how the three models stack up on paper. Figures come from each vendor’s own documentation or model card, except where marked as third-party reported.
| Spec | Claude Opus 4.8 | GPT-5.5 | Gemini 3.5 Flash |
|---|---|---|---|
| Developer | Anthropic | OpenAI | Google DeepMind |
| Release date | May 28, 2026 | April 23, 2026 | May 19, 2026 |
| Context window | 1M tokens (GA) | 1M tokens | Up to 1M tokens (third-party reported) |
| Max output tokens | 128,000 tokens | Not officially disclosed (~128,000 est.) | Not officially disclosed |
| Standard input price | $5.00 / 1M tokens | $5.00 / 1M tokens | $1.50 / 1M tokens |
| Standard output price | $25.00 / 1M tokens | $30.00 / 1M tokens | $9.00 / 1M tokens |
| Premium tier pricing | Fast mode: $10 / $50 per 1M | GPT-5.5 Pro: $30 / $180 per 1M | Not publicly listed |
| SWE-bench Verified | 88.6% (third-party tested) | 88.7% (third-party tested) | Not publicly disclosed |
| Terminal-Bench 2.0 | 69.4% (single third-party source) | 82.7% | Not publicly disclosed |
| Artificial Analysis Intelligence Index | 61.4 (#1 as of June 2026) | 60 at launch | Not tracked in this index yet |
| Prompt caching discount | Up to 90% | Not publicly specified | Not publicly specified |
| Primary deployment surfaces | Claude API, Amazon Bedrock, Vertex AI, Microsoft Foundry | ChatGPT (Plus/Pro/Business/Enterprise), Codex, Responses API | Gemini app, AI Mode, Gemini API, AI Studio, Android Studio, Antigravity, Gemini Enterprise |
| Free consumer tier | No (API-billed) | No (GPT-5.5 specifically is paid-tier) | Yes, Gemini app free tier |
Three things stand out immediately. Claude Opus 4.8 and GPT-5.5 charge identical standard input pricing at $5 per million tokens, but GPT-5.5’s output price runs 20% higher than Claude’s. Gemini 3.5 Flash undercuts both rivals by a wide margin on raw price, consistent with its role as Google’s fast, cost-efficient tier rather than a full flagship release (Google delayed the larger Gemini 3.5 Pro past its original window, according to TechCrunch’s July 2026 report). And none of the three vendors has published a directly comparable agentic tool-use score, so any claim that one model is flatly “better at agents” than another really synthesizes adjacent benchmarks like SWE-bench and Terminal-Bench rather than a single number.
2026 Release Timeline: How Three Flagship Models Leapfrogged Each Other
The sequence matters because it explains why each vendor’s marketing leans on a different comparison point.
GPT-5.5 shipped first, on April 23, 2026, rolling out the same day to ChatGPT Plus, Pro, Business, and Enterprise subscribers, with API access following on April 24. Within 24 hours it topped the Artificial Analysis Intelligence Index with a score of 60, breaking a three-way tie that had persisted for weeks. OpenAI positioned it around coding, research, data analysis, and document production, and shipped it into Codex the same week.
Google answered next. Gemini 3.5 Flash went live May 19 at Google I/O, generally available the same day as the keynote rather than in limited preview. Google’s own release notes describe it as “our most intelligent model for sustained frontier performance on agentic and coding tasks.” It replaced the gemini-3-flash-preview model ID that had been running since December 2025, and became the default model in the Gemini app and AI Mode in Google Search worldwide.
Claude Opus 4.8 arrived last, on May 28, just 41 days after Opus 4.7, the fastest version cadence Anthropic has run to date. It kept Opus 4.7’s 1M-token context window and tool surface, and pricing stayed flat at $5 input and $25 output per million tokens. Anthropic’s benchmark claims pushed the model back to the top of the Intelligence Index at 61.4, a mark the company describes as the first score to cross 60 by a clear margin.
Read together, the timeline is a five-week relay: GPT-5.5 held the top benchmark spot for about a month, Gemini 3.5 Flash reset the price floor without chasing the top spot at all, and Claude Opus 4.8 closed the window by retaking the intelligence crown. As of this comparison’s publication in June 2026, that’s where the leaderboard still sits. No fourth model has displaced Opus 4.8’s position.
What Is Claude Opus 4.8?
Claude Opus 4.8 is Anthropic’s flagship model, released May 28, 2026, as a direct upgrade to Opus 4.7 rather than a ground-up rebuild. It carries a 1-million-token context window by default across the Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry, plus a 128,000-token output cap, according to Anthropic’s own release notes.
Standard pricing held steady at $5 per million input tokens and $25 per million output tokens, the same rate Opus 4.7 charged. Anthropic also ships a Fast mode at $10 input and $50 output per million tokens, which the company says runs three times cheaper than the equivalent fast tier under Opus 4.7. Prompt caching cuts costs by up to 90%, and batch processing knocks another 50% off, both figures pulled directly from Anthropic’s pricing page.
On benchmarks, Anthropic and independent trackers put Opus 4.8 at the top of the Artificial Analysis Intelligence Index with a score of 61.4, alongside a reported Elo of 1,890 on the GDPval-AA economic-tasks benchmark. Third-party testing puts it at 88.6% on SWE-bench Verified and 96.7% on USAMO. Anthropic’s own launch materials also cite an 83.4% OSWorld-Verified score, the company’s stated benchmark for agentic computer-use tasks, though that figure comes from Anthropic’s launch post rather than an independent lab.
Anthropic frames Opus 4.8 around agentic coding, computer use, and enterprise reasoning specifically, rather than general-purpose chat. That positioning shows up in deployment too: it’s available across four major cloud platforms (Claude API direct, Bedrock, Vertex AI, and Foundry) with published default quotas of 20 million input tokens per minute and 4 million output tokens per minute on Bedrock’s mantle tier, scaling to 30 million combined TPM on the runtime tier.
What Is GPT-5.5?
GPT-5.5 is OpenAI’s flagship release from April 23, 2026, described by the company as its first fully retrained base model since GPT-4.5. It rolled out the same day to ChatGPT Plus, Pro, Business, and Enterprise subscribers, with API access in the Responses and Chat Completions APIs following on April 24, and a same-week rollout into Codex, OpenAI’s coding assistant, according to CNBC’s coverage of the launch.
Officially, GPT-5.5 runs a 1-million-token context window at $5 per million input tokens and $30 per million output tokens, per OpenAI’s own launch page. A higher-accuracy variant, GPT-5.5 Pro, uses parallel test-time compute on the same base model and costs $30 input and $180 output per million tokens, available to ChatGPT Pro, Business, and Enterprise users. OpenAI hasn’t published an official max-output-token figure. Third-party trackers estimate it around 128,000 tokens, though that number isn’t confirmed on OpenAI’s own model page.
On benchmarks, secondary sources tracking OpenAI’s rollout independently report the same figures: 88.7% on SWE-bench Verified, 92.4% on MMLU, and 82.7% on Terminal-Bench 2.0. That Terminal-Bench score also appears in tech-insider.org’s own coverage of the GPT-5.5 launch. OpenAI’s official page confirms text and image input support. Some third-party reviewers report broader audio, video, and document input, though that’s not spelled out on OpenAI’s own spec sheet.
GPT-5.5 briefly topped the Artificial Analysis Intelligence Index at a score of 60 within a day of launch, breaking what one launch-day report described as a three-way tie that had held for weeks, before Claude Opus 4.8 overtook it five weeks later.
What Is Gemini 3.5 Flash?
Gemini 3.5 Flash is Google DeepMind’s first model in the Gemini 3.5 family, released May 19, 2026, at Google I/O. Unlike the other two models here, it launched as the fast, cost-efficient tier rather than a top-of-line flagship. Google has not shipped a Gemini 3.5 Pro as of this writing. TechCrunch reported in July 2026 that Google released three smaller Gemini updates (3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber) while the Pro flagship remained delayed with no announced timeline.
Google’s own changelog describes Gemini 3.5 Flash as “our most intelligent model for sustained frontier performance on agentic and coding tasks,” and says it beats the larger, previous-generation Gemini 3.1 Pro on several agentic and coding tests despite running in the smaller Flash tier. It shipped generally available the same day as its announcement, with a stable model ID (gemini-3.5-flash) replacing the gemini-3-flash-preview identifier that had been running since December 2025. Google has listed a retirement date no earlier than May 19, 2027.
Pricing, corroborated by two independent trackers, runs $1.50 per million input tokens and $9.00 per million output tokens, roughly a third of Claude’s rate and a fifth of GPT-5.5’s on the output side. Google has not published an official context-window or max-output figure specifically for Gemini 3.5 Flash. Third-party trackers report figures up to 1 million tokens, consistent with the rest of the Gemini 3.x line, but that number isn’t confirmed on Google’s own model card as of this writing.
Availability is the broadest of the three: the Gemini app free tier and AI Mode in Google Search for consumers, Google Antigravity and the Gemini API in AI Studio and Android Studio for developers, and the Gemini Enterprise Agent Platform for business customers, all listed directly on Google’s own announcement post.
Pricing Breakdown: Claude Opus 4.8 vs GPT-5.5 vs Gemini 3.5 Flash Cost
| Pricing factor | Claude Opus 4.8 | GPT-5.5 | Gemini 3.5 Flash |
|---|---|---|---|
| Input, per 1M tokens | $5.00 | $5.00 | $1.50 |
| Output, per 1M tokens | $25.00 | $30.00 | $9.00 |
| Premium/fast tier input | $10.00 (Fast mode) | $30.00 (GPT-5.5 Pro) | Not listed |
| Premium/fast tier output | $50.00 (Fast mode) | $180.00 (GPT-5.5 Pro) | Not listed |
| Prompt caching discount | Up to 90% | Not published | Not published |
| Batch processing discount | 50% | Not published | Not published |
| Cost for 50M output tokens/mo (standard rate) | $1,250 | $1,500 | $450 |
| Free tier | No | No | Yes (Gemini app) |
The clearest number in this whole comparison is the output-price gap: GPT-5.5 charges $30 per million output tokens, Gemini 3.5 Flash charges $9, and the difference between them is exactly $21. That’s before caching or batch discounts, which currently only Anthropic has published concrete percentages for.
For teams running heavy output workloads, like long-form generation, detailed code diffs, or multi-step agent transcripts, that $21-per-million gap compounds fast. Generating 50 million output tokens a month, a realistic volume for a mid-size coding-agent product, costs $1,500 on GPT-5.5, $1,250 on Claude Opus 4.8, and $450 on Gemini 3.5 Flash, using each vendor’s own published standard rate. That’s a real, calculable difference, not a rounding error.
Input pricing tells a different story. Claude Opus 4.8 and GPT-5.5 both charge exactly $5 per million input tokens, per their respective official pricing pages, while Gemini 3.5 Flash charges $1.50, less than a third of either rival. For retrieval-heavy or document-analysis workloads that push large amounts of context into every call, Gemini’s input pricing advantage matters more than its output pricing, since those workloads often generate short outputs relative to input size.
Premium tiers complicate direct comparison. Anthropic’s Fast mode ($10/$50 per million) targets latency-sensitive use cases, not higher accuracy. OpenAI’s GPT-5.5 Pro ($30/$180 per million) targets higher accuracy via extra test-time compute, a fundamentally different tradeoff. Google hasn’t published a premium tier for Gemini 3.5 Flash at all, at least not yet, since the higher-end Gemini 3.5 Pro remains unreleased.
Benchmark Results: SWE-bench, Terminal-Bench and the Intelligence Index
Benchmark numbers for all three models come from a mix of vendor claims and independent trackers, so treat any single score as directional rather than exact, especially across different testing methodologies.
| Benchmark | Claude Opus 4.8 | GPT-5.5 | Gemini 3.5 Flash |
|---|---|---|---|
| Artificial Analysis Intelligence Index | 61.4 (#1) | 60 at launch | Not tracked yet |
| SWE-bench Verified | 88.6% | 88.7% | Not disclosed |
| Terminal-Bench 2.0 | 69.4% (single source) | 82.7% | Not disclosed |
| MMLU | Not disclosed in this research | 92.4% | Not disclosed |
| GDPval-AA | Elo 1,890 | Not disclosed | Not disclosed |
| OSWorld-Verified | 83.4% (Anthropic-reported) | Not disclosed | Not disclosed |
On SWE-bench Verified, the industry’s most-cited real-world coding benchmark, tracked independently at swebench.com, Claude Opus 4.8 and GPT-5.5 land within a tenth of a point of each other: 88.6% versus 88.7%, per third-party testing. Google has not published a Gemini 3.5 Flash SWE-bench score.
On Terminal-Bench 2.0, which tests multi-step command-line and agentic task completion, GPT-5.5 posts 82.7%, a figure repeated consistently across multiple independent writeups and tech-insider’s own GPT-5.5 launch coverage. One third-party comparison puts Claude at 69.4% on the same test, though that’s a single secondary source rather than an Anthropic-confirmed number, so treat it with more caution than the SWE-bench figures.
The Artificial Analysis Intelligence Index, a composite score spanning reasoning, coding, agentic tool use, science, and long-context retrieval, currently ranks Claude Opus 4.8 first at 61.4. GPT-5.5 briefly held the top spot at 60 immediately after its April launch. Gemini 3.5 Flash isn’t confirmed in the same index as of this writing, since Google’s benchmark claims for the model center on its own internal coding and agentic test suite rather than the third-party index the other two vendors get measured against.
Two more Anthropic-specific figures worth noting: a GDPval-AA Elo of 1,890 on economic-task evaluation, and an OSWorld-Verified score of 83.4% for agentic computer-use tasks, both from Anthropic’s own launch materials rather than independent verification. Take those two as directional rather than final, the same caveat that applies to any vendor-reported benchmark.
Context Windows and Output Limits Compared
All three vendors now anchor their flagship-tier models around a 1-million-token context window, at least on paper, a sharp jump from the 128,000 to 200,000-token windows that were standard just two years earlier. Claude Opus 4.8’s 1M-token window is generally available today across the Claude API, Bedrock, Vertex AI, and Microsoft Foundry, confirmed directly in Anthropic’s platform release notes. GPT-5.5 matches it at 1M tokens per OpenAI’s own launch page. Gemini 3.5 Flash is reported at similar levels by third-party trackers, though Google’s own model card doesn’t spell out an exact figure specifically for the Flash tier as of this writing.
Output limits are where the picture gets murkier. Anthropic publishes a hard 128,000-token output cap for Opus 4.8. OpenAI hasn’t published an equivalent number for GPT-5.5. Third-party estimates cluster around the same 128,000-token range, but that’s an inference from testing, not a documented spec. Google hasn’t published a max-output figure for Gemini 3.5 Flash either.
In practice, a 1M-token context window rarely gets used at full capacity, and vendors know it. What matters more for most production use is how each model handles the middle of a long context and how pricing scales as prompts grow. Anthropic’s Opus 4.6 announcement, the generation before 4.8, disclosed that prompts exceeding 200,000 tokens incur premium pricing of $10 input and $37.50 output per million tokens rather than the standard rate. Whether that same tiered structure still applies to Opus 4.8 specifically isn’t confirmed in Anthropic’s 4.8 announcement, so budget-conscious teams running very long prompts should check current pricing before assuming the standard rate applies at full context length.
Multimodal Capabilities Compared
Multimodal support is the least-documented spec across all three models, and vendors describe it inconsistently.
Claude Opus 4.8 supports vision input as part of its standard tool surface, carried over from Opus 4.7, according to Anthropic’s release notes. Anthropic’s public materials reviewed for this comparison didn’t document audio or video input support specifically for the model.
GPT-5.5’s official OpenAI launch page confirms text and image input support through the API. Some third-party reviewers describe broader input modalities, including audio, video, and document formats, but that’s not spelled out on OpenAI’s own spec sheet for GPT-5.5 specifically, so treat the broader claims as unconfirmed until OpenAI documents them directly.
Gemini has historically led on native multimodality among the three vendors, and Google’s Gemini 3.5 Flash announcement emphasizes broad availability across consumer, developer, and enterprise surfaces rather than detailing a modality matrix. Google’s own materials reviewed for this comparison didn’t break out a specific vision, audio, and video input-output table for the Flash tier.
The practical takeaway: if your workload depends heavily on a specific modality, such as audio transcription pipelines, video understanding, or complex document parsing, test the actual API response for that modality directly rather than relying on marketing copy from any of the three vendors. Published multimodal claims in this space consistently run ahead of what’s independently documented.
Agentic and Tool-Use Performance
Every vendor markets its 2026 flagship as an “agentic” model, but the benchmarks used to back that claim differ enough across Anthropic, OpenAI, and Google that direct comparison is difficult.
Anthropic leans on OSWorld-Verified (83.4%, per its own launch post) and GDPval-AA (Elo 1,890) as its agentic proof points, both measuring computer-use and economically-relevant task completion rather than pure coding. The company also kept Opus 4.8’s tool-calling surface identical to Opus 4.7’s, meaning existing agent orchestration code built for the previous version should carry over without changes, according to Anthropic’s own release notes.
OpenAI’s agentic claims for GPT-5.5 center on Terminal-Bench 2.0 (82.7%) and its integration into Codex, OpenAI’s coding-focused agent product, which shipped the model the same week as the ChatGPT rollout. SWE-bench Verified, at 88.7% per third-party testing, is the closest thing to a shared coding metric across all three vendors, though it measures code-fixing accuracy rather than broader agentic behavior like multi-app tool orchestration.
Google’s agentic pitch for Gemini 3.5 Flash rests on its own internal coding and agentic test suite rather than SWE-bench or Terminal-Bench specifically, plus its integration into Google Antigravity, described in Google’s own materials as an “agent-first” development platform. That framing makes Gemini harder to place directly against the other two on a shared numeric scale, even though Google’s own changelog claims it beats the larger Gemini 3.1 Pro on agentic and coding tasks.
The bottom line: SWE-bench Verified is the only benchmark with numbers for two of the three models here, Claude and GPT-5.5, essentially tied at 88.6% and 88.7%, and Gemini 3.5 Flash simply hasn’t published a comparable figure yet. Anyone choosing based purely on agentic benchmark supremacy is working with an incomplete data set, regardless of which vendor’s marketing they read.
Enterprise Deployment: Availability, Quotas and Cloud Marketplaces
Where a model is actually available often matters more to enterprise buyers than raw benchmark scores, since procurement, compliance, and existing cloud contracts frequently decide the shortlist before performance testing even starts.
Claude Opus 4.8 is available through four channels: the direct Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry, according to Anthropic’s own announcement. That’s the widest multi-cloud spread of the three models here, letting enterprises already committed to AWS, Google Cloud, or Azure procurement run Claude without a separate vendor relationship. Amazon’s own Bedrock documentation lists default quotas of 20 million input tokens per minute and 4 million output tokens per minute on the standard tier, scaling to 30 million combined TPM on Bedrock’s runtime tier per supported region.
GPT-5.5 stays inside OpenAI’s own ecosystem: ChatGPT (Plus, Pro, Business, and Enterprise tiers), Codex, and the Responses and Chat Completions APIs directly through OpenAI, per the company’s launch announcement. There’s no Bedrock- or Vertex-style third-party cloud marketplace listing found in the sources reviewed for this comparison, meaning enterprises need a direct OpenAI relationship or an API gateway layered on top.
Gemini 3.5 Flash has the broadest surface area of the three, spanning the free consumer Gemini app, AI Mode in Google Search, the Gemini API through AI Studio and Android Studio for developers, Google Antigravity for agent-first development, and the Gemini Enterprise Agent Platform plus Gemini Enterprise app for business customers, all listed directly on Google’s announcement. Google’s Cloud blog specifically notes that business users can start using Gemini 3.5 Flash in the Gemini Enterprise app to help discover, create, and use Google AI in their workflows.
For regulated industries specifically, Claude’s presence across three separate hyperscaler marketplaces (Bedrock, Vertex AI, and Foundry) gives compliance and data-residency teams more existing-contract options than either single-cloud rival offers today.
Real-World Use Cases: How Teams Are Choosing Between These Models
Six patterns show up repeatedly in how these three models actually get deployed, based on each vendor’s own documented integrations rather than speculative use cases.
- Coding agents and CLI tools. OpenAI shipped GPT-5.5 into Codex the same week as its ChatGPT rollout, and the model’s 82.7% Terminal-Bench 2.0 score reflects that focus on command-line and multi-step coding tasks. Teams building autonomous coding agents that need to execute shell commands, not just suggest code, lean toward this integration path.
- Multi-cloud enterprise deployment. Claude Opus 4.8’s availability across Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry means a bank or healthcare system already running workloads on any of the three major hyperscalers can add Claude without a new vendor security review.
- Consumer search and everyday assistant use. Gemini 3.5 Flash became the default model behind the Gemini app and AI Mode in Google Search worldwide the day it launched, according to Google’s own blog post, putting it in front of what Google describes as billions of people globally without any opt-in required.
- Mobile and IDE developer tooling. Gemini 3.5 Flash ships inside Android Studio directly, giving mobile developers in-editor access without a separate API integration step, plus Google Antigravity for teams building agent-first workflows from scratch.
- Enterprise agent platforms. Businesses standardizing on a single vendor’s agent tooling can run Gemini 3.5 Flash through the Gemini Enterprise Agent Platform, or Claude Opus 4.8 through Bedrock’s or Foundry’s respective agent frameworks, depending on which cloud already hosts their data.
- High-volume, cost-sensitive inference. At $1.50 input and $9.00 output per million tokens, Gemini 3.5 Flash is the clear choice for workloads where call volume matters more than squeezing out the last few benchmark points, like customer-support triage or first-pass document classification before escalating harder cases to a pricier model.
These are documented deployment patterns pulled from each vendor’s own materials, not hypothetical scenarios, and they line up with the pricing and benchmark data covered above: OpenAI is leaning into coding agents, Google is leaning into ubiquity and low cost, and Anthropic is leaning into multi-cloud enterprise reach.
Pros and Cons of Each Model
Claude Opus 4.8 Pros and Cons
Pros:
- Leads the Artificial Analysis Intelligence Index outright at 61.4, and ties GPT-5.5 for the top SWE-bench Verified score (88.6%)
- Widest enterprise cloud reach: available on Bedrock, Vertex AI, and Microsoft Foundry in addition to the direct API
- Prompt caching cuts costs up to 90%, the only one of the three vendors to publish a concrete caching discount
- 128,000-token output cap is officially documented, not estimated
Cons:
- Most expensive output pricing among the three after Gemini’s much lower rate ($25 per million versus Gemini’s $9)
- No free consumer chat tier tied to this specific model
- Some headline benchmarks, including OSWorld-Verified, come from Anthropic’s own launch materials rather than independent labs
GPT-5.5 Pros and Cons
Pros:
- Matches Claude on SWE-bench Verified (88.7%) and leads clearly on Terminal-Bench 2.0 (82.7%)
- Deepest ChatGPT consumer integration, reaching Plus, Pro, Business, and Enterprise tiers instantly at launch
- GPT-5.5 Pro variant offers a documented higher-accuracy tier via test-time compute for teams that need it
Cons:
- Highest standard output price of the three ($30 per million), a $21 gap versus Gemini 3.5 Flash
- No published max-output-token figure or agentic tool-use benchmark from OpenAI directly
- Deployment stays inside OpenAI’s own ecosystem, with no Bedrock- or Vertex-style multi-cloud listing found in this research
Gemini 3.5 Flash Pros and Cons
Pros:
- Cheapest of the three by a wide margin: $1.50 input and $9.00 output per million tokens
- Broadest availability, spanning a free consumer tier, Search integration, IDE tooling, and enterprise agent platforms
- Reportedly beats Google’s own larger Gemini 3.1 Pro on coding and agentic tasks despite the lower Flash-tier price
Cons:
- No published SWE-bench, Terminal-Bench, or Artificial Analysis Index score, making direct benchmark comparison incomplete
- Context window and max-output figures aren’t officially confirmed by Google, only estimated by third-party trackers
- The higher-end Gemini 3.5 Pro remains unreleased, so there’s no like-for-like flagship comparison against Claude Opus 4.8 or GPT-5.5 Pro yet
Migration Guide: Switching Between Claude, GPT and Gemini APIs
Moving a production workload from one of these three models to another isn’t a drop-in swap, even though all three now converge around similar context-window sizes and per-token pricing structures. Here’s what actually changes.
API structure and authentication. Anthropic’s Claude API uses its Messages endpoint with an x-api-key header. GPT-5.5 is available through both the newer Responses API and the older Chat Completions API, authenticated with a bearer token. Google’s Gemini API authenticates through either an API key in AI Studio or full IAM-based auth on Vertex AI, depending on which surface you’re building against. None of the three request or response formats are interchangeable without a translation layer.
| Migration factor | Claude Opus 4.8 | GPT-5.5 | Gemini 3.5 Flash |
|---|---|---|---|
| API endpoint style | Messages API | Responses API or Chat Completions API | generateContent (Gemini API) |
| Auth method | x-api-key header | Bearer token | API key (AI Studio) or IAM (Vertex AI) |
| Tool/function-calling format | Tool-use blocks (unchanged since Opus 4.7) | Function-calling schema | Function-declarations format |
| Documented max output | 128,000 tokens | Not officially documented | Not officially documented |
| Vendor-specific cost lever | Prompt caching (up to 90% off) | Not published | Not published |
# Simplified request shape, illustrative only
# Claude Opus 4.8 (Anthropic Messages API)
POST https://api.anthropic.com/v1/messages
headers: { "x-api-key": API_KEY, "anthropic-version": "2023-06-01" }
body: {
"model": "claude-opus-4-8",
"max_tokens": 1024,
"messages": [{"role": "user", "content": "..."}]
}
# GPT-5.5 (OpenAI Responses API)
POST https://api.openai.com/v1/responses
headers: { "Authorization": "Bearer API_KEY" }
body: {
"model": "gpt-5.5",
"input": "..."
}
# Gemini 3.5 Flash (Google Gemini API)
POST https://generativelanguage.googleapis.com/v1/models/gemini-3.5-flash:generateContent
headers: { "x-goog-api-key": API_KEY }
body: {
"contents": [{"parts": [{"text": "..."}]}]
}Tokenizers differ. Each vendor tokenizes text with its own scheme, so a prompt that costs 1,000 tokens on one model won’t necessarily cost 1,000 tokens on another. Cost estimates should always be built from the target model’s actual tokenizer, not carried over from whichever model you’re migrating away from.
Tool-calling formats differ. Anthropic kept Opus 4.8’s tool-calling surface identical to Opus 4.7’s, per its release notes, but that surface doesn’t match OpenAI’s function-calling schema or Gemini’s function-declarations format. Agent orchestration code that loops on tool calls needs a per-vendor adapter, not just a model-name swap.
Context and output budgeting. All three models now claim roughly 1M-token context windows, but only Claude Opus 4.8, at 128,000 tokens, has a firmly documented max-output cap among the three. If your workload generates long outputs, such as full-file code rewrites or long-form reports, test actual output length limits on the target model before migrating rather than assuming parity.
Pricing recalculation. Because Gemini 3.5 Flash costs roughly a third of Claude’s input price and a fifth of GPT-5.5’s output price, a straight model swap can change unit economics dramatically even if code changes are minimal. Anthropic’s prompt-caching discount, up to 90%, and batch-processing discount, 50%, aren’t guaranteed to have direct equivalents on the other two platforms, so a cost model built around Claude’s caching behavior may not transfer cleanly.
Practical migration path: run the same evaluation set, ideally your own production prompts rather than a public benchmark, against all three models before committing, since published benchmark scores measure general capability, not your specific prompt patterns or output-length requirements.
Which Model Should You Choose? 5 Use-Case Recommendations
- Building a coding agent or CLI-driven dev tool: choose GPT-5.5. Its 82.7% Terminal-Bench 2.0 score and direct Codex integration make it the most benchmarked option specifically for command-line and multi-step coding tasks among the three.
- Running high-volume, cost-sensitive inference: choose Gemini 3.5 Flash. At $1.50 input and $9.00 output per million tokens, it’s roughly a third to a fifth the cost of the other two, and Google’s own claims put it ahead of the larger Gemini 3.1 Pro on coding despite the lower price.
- Deploying inside a regulated, multi-cloud enterprise environment: choose Claude Opus 4.8. Its availability on Bedrock, Vertex AI, and Microsoft Foundry, combined with documented per-region TPM quotas, fits organizations that need to keep AI workloads inside an already-approved cloud contract.
- Building a consumer-facing product that needs free-tier reach: choose Gemini 3.5 Flash. It’s the only one of the three with a genuinely free consumer tier, the Gemini app, rather than a paid-subscription gate, and it’s already the default model behind AI Mode in Google Search.
- Processing very long documents where output cost dominates the bill: choose Claude Opus 4.8. The documented 128,000-token output cap plus up to 90% prompt-caching discount gives the clearest, most predictable cost model for repeated long-context calls among the three, since the other two haven’t published equivalent caching numbers.
Where These Three Fit in the Wider 2026 AI Model Market
Claude Opus 4.8, GPT-5.5, and Gemini 3.5 Flash don’t exist in isolation, and treating this three-way comparison as the entire market misses useful context on both ends of the price spectrum.
Anthropic has already shipped a tier above Opus 4.8: Claude Fable 5, priced at $10 input and $50 output per million tokens on at least one tracked leaderboard, roughly double Opus 4.8’s standard rate. That’s a preview of where Anthropic’s pricing goes for teams that need more than the flagship covered in this comparison. On the budget end, open-weight models like MiniMax M3 undercut even Gemini 3.5 Flash, pricing at $0.60 input and $1.80 output per million tokens, though without the same multi-cloud enterprise deployment options that Claude Opus 4.8 offers across Bedrock, Vertex AI, and Foundry.
That range, from roughly $0.60 to $50 per million tokens depending on tier, is worth keeping in mind when evaluating this comparison. Claude Opus 4.8, GPT-5.5, and Gemini 3.5 Flash represent the current mainstream flagship-to-fast tier, not the cheapest or the most expensive options on the market. Teams with extreme cost sensitivity or extreme accuracy requirements may find a better fit outside this specific three-way comparison, even though these three remain the most-searched, most-benchmarked options as of mid-2026.
The Verdict: Claude Opus 4.8 vs GPT-5.5 vs Gemini 3.5 Flash
There’s no single winner here, and the data doesn’t support pretending otherwise. Claude Opus 4.8 currently leads the one benchmark all three vendors implicitly compete on, the Artificial Analysis Intelligence Index, at 61.4, and it backs that with the broadest enterprise cloud footprint of the three. GPT-5.5 essentially ties Claude on SWE-bench Verified (88.7% versus 88.6%) and leads clearly on Terminal-Bench 2.0 (82.7%), making it the strongest pick specifically for coding-agent workloads, but it’s also the most expensive of the three on output pricing at $30 per million tokens. Gemini 3.5 Flash can’t match either rival on published benchmark depth, since Google simply hasn’t released comparable SWE-bench or Intelligence Index numbers, but it wins decisively on price and reach, undercutting Claude’s output cost by nearly two-thirds and GPT-5.5’s by 70%.
If price per token were the only variable, Gemini 3.5 Flash would win outright. If benchmark supremacy were the only variable, Claude Opus 4.8 edges ahead on the composite index while GPT-5.5 edges ahead on raw coding tests. In practice, the deciding factor for most teams will be deployment fit: which cloud you’re already contracted with, whether you need Codex-style CLI integration, and whether your workload is output-heavy, where Claude’s caching and Gemini’s low output price both matter, or input-heavy, where Gemini’s $1.50 rate matters most.
The one number worth remembering from this whole comparison is the $21 output-price gap between GPT-5.5’s $30 and Gemini 3.5 Flash’s $9 per million tokens, with Claude Opus 4.8 sitting almost exactly in the middle at $25. That gap alone should be enough to justify testing more than one model against your actual workload before committing. Three different flagship-tier answers to “what should this cost” from three credible vendors is a sign the market hasn’t settled, not that any one price is simply correct.
Frequently Asked Questions
Which is cheaper: Claude Opus 4.8, GPT-5.5, or Gemini 3.5 Flash?
Gemini 3.5 Flash is the cheapest of the three on both input and output pricing, at $1.50 and $9.00 per million tokens respectively. Claude Opus 4.8 costs $5 input and $25 output, and GPT-5.5 costs $5 input and $30 output, per each vendor’s official pricing page.
Which model scores highest on SWE-bench?
GPT-5.5 and Claude Opus 4.8 are effectively tied, at 88.7% and 88.6% respectively on SWE-bench Verified, according to independent third-party testing. Google hasn’t published a Gemini 3.5 Flash SWE-bench score.
Does Gemini 3.5 Flash have a free tier?
Yes. Gemini 3.5 Flash is available at no cost through the Gemini app and AI Mode in Google Search, per Google’s own announcement. Claude Opus 4.8 and GPT-5.5 are both paid, either through API billing or a ChatGPT subscription tier.
What is the context window for each model?
Claude Opus 4.8 and GPT-5.5 both officially support 1-million-token context windows, confirmed on Anthropic’s and OpenAI’s own documentation respectively. Gemini 3.5 Flash is reported at similar levels by third-party trackers, but Google hasn’t published an exact figure specifically for the Flash tier as of this writing.
Can I use Claude Opus 4.8 through AWS or Azure?
Yes. Claude Opus 4.8 is available on Amazon Bedrock and Microsoft Foundry, in addition to Anthropic’s direct API and Google Cloud Vertex AI, making it the most multi-cloud-friendly of the three models covered here.
Is GPT-5.5 available in GitHub Copilot?
Some third-party roundups report GPT-5.5 integration into Copilot, though this isn’t confirmed on OpenAI’s own GPT-5.5 launch page, which specifically names ChatGPT and Codex as launch-day integrations. Check GitHub’s own model documentation for current Copilot model availability before building around it.
Which model is best for coding agents specifically?
GPT-5.5 posts the strongest documented score on Terminal-Bench 2.0 (82.7%), a benchmark built around multi-step command-line and agentic coding tasks, and it shipped directly into Codex at launch. Claude Opus 4.8 is close behind on SWE-bench Verified and offers a wider range of cloud deployment options for agent infrastructure.
Will Gemini 3.5 Pro change this comparison?
Possibly. As of this comparison’s publication, Google has not released Gemini 3.5 Pro. TechCrunch reported in July 2026 that Google shipped smaller Flash-tier updates instead while the Pro flagship remained delayed with no confirmed timeline. A Gemini 3.5 Pro launch would likely reset the benchmark comparison against Claude Opus 4.8 and GPT-5.5 Pro’s top-line scores.
Related Coverage
- Claude Opus 4.8 Hits 61.4, Tops AI Leaderboard [2026]
- GPT-5.5 Launch: 82.7% Terminal-Bench, $5 API [2026]
- Claude vs Gemini vs ChatGPT: $18 Output Price Gap [2026]
- Grok 4.5 vs GPT-5.6 vs Gemini 3.1 Pro: $24 Price Gap [2026]
- DeepSeek V4 vs GLM-5.2 vs Qwen: 10x Price Gap [2026]
- Phi-4 Mini vs Gemma 3 vs Llama 3.2: 128K vs 32K [2026]
- OpenAI Retires 4 GPT Models as GPT-4o Holds 37.6% [2026]
