LLM Reference

Claude Opus 4.7 vs GPT-5.5

Claude Opus 4.7 (2026) and GPT-5.5 (2026) are frontier-tier reasoning models from Anthropic and OpenAI. Claude Opus 4.7 ships a 1m-token context window, while GPT-5.5 ships a 1.05m-token context window. On SWE-bench Verified, Claude Opus 4.7 leads by 5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Pick Claude Opus 4.7 for coding; GPT-5.5 is better when coding workflow support matters more.

Decision scorecard

Local evidence first
SignalClaude Opus 4.7GPT-5.5
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1m1.05m
Cheapest output$25/1M tokens$30/1M tokens
Provider routes6 tracked3 tracked
Shared benchmarksSWE-bench Verified leader9 rows

Decision tradeoffs

Choose Claude Opus 4.7 when...
  • Claude Opus 4.7 holds a shared-benchmark lead on SWE-bench Verified, ahead by 5 points.
  • Claude Opus 4.7 has the lower cheapest tracked output price at $25/1M tokens.
  • Claude Opus 4.7 has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Claude Opus 4.7 for Coding, RAG, and Agents.
Choose GPT-5.5 when...
  • GPT-5.5 holds a shared-benchmark lead on Terminal-Bench 2.0, ahead by 13.3 points.
  • GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags GPT-5.5 for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Claude Opus 4.7

Claude Opus 4.7

$10,250

Cheapest tracked route/tier: Anthropic

GPT-5.5

$11,500

Cheapest tracked route/tier: OpenAI API 0-272K input tokens

Estimated monthly gap: $1,250. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Claude Opus 4.7 -> GPT-5.5
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • GPT-5.5 is $5/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
GPT-5.5 -> Claude Opus 4.7
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Claude Opus 4.7 is $5/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2026-04-162026-04-23
Context window1m1.05m
Parameters
Architecturedecoder onlydecoder only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
Commercial useCommercial use with conditionsCommercial use with conditions
Knowledge cutoff2026-012025-12

Pricing and availability

Pricing attributeClaude Opus 4.7GPT-5.5
Input price$5/1M tokens
0-272K input tokens
$5/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
0-272,000t
$5/1M tokens
272K+ input tokens
$8/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
272,000t+
$10/1M tokens
Output price$25/1M tokens
0-272K input tokens
$30/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
0-272,000t
$30/1M tokens
272K+ input tokens
$36/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
272,000t+
$45/1M tokens
Providers

Capabilities

CapabilityClaude Opus 4.7GPT-5.5
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkClaude Opus 4.7GPT-5.5
SWE-bench Verified87.682.6
Google-Proof Q&A94.293.6
Humanity's Last Exam54.741.4
Chatbot Arena1503.01488.0
Terminal-Bench 2.069.482.7
ARC-AGI-275.885.0
SWE-bench Pro64.358.6
BrowseComp79.384.4
MCP-Atlas77.375.3

Deep dive

On shared benchmark coverage, SWE-bench Verified has Claude Opus 4.7 at 87.6 and GPT-5.5 at 82.6, with Claude Opus 4.7 ahead by 5 points; Google-Proof Q&A has Claude Opus 4.7 at 94.2 and GPT-5.5 at 93.6, with Claude Opus 4.7 ahead by 0.6 points; Humanity's Last Exam has Claude Opus 4.7 at 54.7 and GPT-5.5 at 41.4, with Claude Opus 4.7 ahead by 13.3 points. The largest visible gap is 13.3 points on Humanity's Last Exam, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint is close: both models cover vision, multimodal input, reasoning mode, function calling, and tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, Claude Opus 4.7 lists $5/1M input and $25/1M output tokens on the cheapest tracked provider, while GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 0-272,000t is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output; 272,000t+ is $10/1M input and $45/1M output. A 70/30 input-output blend puts Claude Opus 4.7 lower by about $1.50 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 6 providers versus 3, so concentration risk also matters.

Choose Claude Opus 4.7 when coding workflow support and broader provider choice are central to the workload. Choose GPT-5.5 when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, Claude Opus 4.7 or GPT-5.5?

GPT-5.5 supports 1.05m tokens, while Claude Opus 4.7 supports 1m tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Claude Opus 4.7 or GPT-5.5?

Claude Opus 4.7 lists $5/1M input and $25/1M output tokens on the cheapest tracked provider. GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 0-272,000t is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output; 272,000t+ is $10/1M input and $45/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.

Is Claude Opus 4.7 or GPT-5.5 open source?

Claude Opus 4.7 is listed under Proprietary. GPT-5.5 is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Claude Opus 4.7 or GPT-5.5?

Both Claude Opus 4.7 and GPT-5.5 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Claude Opus 4.7 or GPT-5.5?

Both Claude Opus 4.7 and GPT-5.5 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run Claude Opus 4.7 and GPT-5.5?

Claude Opus 4.7 is available on Anthropic, AWS Bedrock, GCP Vertex AI, Microsoft Foundry, and OpenRouter. GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.