GPT-5.5 Pro vs Kimi K2.7-Code
GPT-5.5 Pro (2026) and Kimi K2.7-Code (2026) compare a standalone API model against a coding-specialized model. GPT-5.5 Pro ships a 1.05m-token context window, while Kimi K2.7-Code ships a 262k-token context window. On GeneBench-Pro, GPT-5.5 Pro leads by 18.2 pts. On pricing, Kimi K2.7-Code costs $0.61/1M input tokens versus $30/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GPT-5.5 Pro is standalone API model, while Kimi K2.7-Code is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.5 Pro | Kimi K2.7-Code |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1.05m | 262k |
| Cheapest output | $180/1M tokens | $3.07/1M tokens |
| Provider routes | 3 tracked | 2 tracked |
| Shared benchmarks | GeneBench-Pro leader | 2 shared |
Decision tradeoffs
- GPT-5.5 Pro holds a shared-benchmark lead on GeneBench-Pro, ahead by 18.2 points.
- GPT-5.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.5 Pro uniquely exposes Code execution in local model data.
- Local decision data tags GPT-5.5 Pro for Coding, RAG, and Agents.
- Kimi K2.7-Code holds a shared-benchmark lead on MCP-Atlas, ahead by 0.7 points.
- Kimi K2.7-Code has the lower cheapest tracked output price at $3.07/1M tokens.
- Local decision data tags Kimi K2.7-Code 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.
GPT-5.5 Pro
$69,000
Cheapest tracked route/tier: OpenAI API <=272K tokens (standard)
Kimi K2.7-Code
$1,257
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $67,743. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Kimi K2.7-Code is $177/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Code execution before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.5 Pro is $177/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 Pro adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2026-06-12 |
| Context window | 1.05m | 262k |
| Parameters | — | 1T |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | MITOSI-approved |
| Openness | Proprietary | Open source |
| Weights | Not released | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2025-12 | - |
Pricing and availability
| Pricing attribute | GPT-5.5 Pro | Kimi K2.7-Code |
|---|---|---|
| Input price | $30/1M tokens | $0.61/1M tokens |
| Output price | $180/1M tokens | $3.07/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 Pro | Kimi K2.7-Code |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5.5 Pro | Kimi K2.7-Code |
|---|---|---|
| GeneBench-Pro | 20.5 | 2.3 |
| MCP-Atlas | 75.3 | 76.0 |
Deep dive
On shared benchmark coverage, GeneBench-Pro has GPT-5.5 Pro at 20.5 and Kimi K2.7-Code at 2.3, with GPT-5.5 Pro ahead by 18.2 points; MCP-Atlas has GPT-5.5 Pro at 75.3 and Kimi K2.7-Code at 76, with Kimi K2.7-Code ahead by 0.7 points. The largest visible gap is 18.2 points on GeneBench-Pro, 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 differs most on code execution: GPT-5.5 Pro. Both models share vision, multimodal input, reasoning mode, and function calling, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.5 Pro lists $30/1M input and $180/1M output tokens on the cheapest tracked provider, while Kimi K2.7-Code lists $0.61/1M input and $3.07/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.7-Code lower by about $73.65 per million blended tokens. Availability is 3 providers versus 2, so concentration risk also matters.
Choose GPT-5.5 Pro when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Kimi K2.7-Code when coding workflow support and lower input-token cost 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, GPT-5.5 Pro or Kimi K2.7-Code?
GPT-5.5 Pro supports 1.05m tokens, while Kimi K2.7-Code supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-5.5 Pro or Kimi K2.7-Code?
Kimi K2.7-Code is cheaper on tracked token pricing. GPT-5.5 Pro costs $30/1M input and $180/1M output tokens. Kimi K2.7-Code costs $0.61/1M input and $3.07/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 Pro or Kimi K2.7-Code open source?
GPT-5.5 Pro is listed under Proprietary. Kimi K2.7-Code is listed under MIT. 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, GPT-5.5 Pro or Kimi K2.7-Code?
Both GPT-5.5 Pro and Kimi K2.7-Code 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, GPT-5.5 Pro or Kimi K2.7-Code?
Both GPT-5.5 Pro and Kimi K2.7-Code 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 GPT-5.5 Pro and Kimi K2.7-Code?
GPT-5.5 Pro is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Kimi K2.7-Code is available on Moonshot AI Kimi and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.