GPT-5.3-Codex vs Kimi K2.7-Code
GPT-5.3-Codex (2026) and Kimi K2.7-Code (2026) are agentic coding models from OpenAI and Moonshot AI. GPT-5.3-Codex ships a 400k-token context window, while Kimi K2.7-Code ships a 262k-token context window. On pricing, Kimi K2.7-Code costs $0.95/1M input tokens versus $1.75/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Kimi K2.7-Code is ~84% cheaper at $0.95/1M; pay for GPT-5.3-Codex only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-5.3-Codex | Kimi K2.7-Code |
|---|---|---|
| Best for | custom coding agents, code generation, and tool loops | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 400k | 262k |
| Cheapest output | $14/1M tokens | $4/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.3-Codex uniquely exposes Code execution and Computer use in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
- Kimi K2.7-Code has the lower cheapest tracked output price at $4/1M tokens.
- Kimi K2.7-Code uniquely exposes Multimodal in local model data.
- 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-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Kimi K2.7-Code
$1,760
Cheapest tracked route/tier: Moonshot AI Kimi
Estimated monthly gap: $3,140. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.3-Codex and Kimi K2.7-Code; plan for SDK, billing, or endpoint changes.
- Kimi K2.7-Code is $10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Code execution and Computer use before moving production traffic.
- Kimi K2.7-Code adds Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Kimi K2.7-Code and GPT-5.3-Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.3-Codex is $10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Multimodal before moving production traffic.
- GPT-5.3-Codex adds Code execution and Computer use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-05 | 2026-06-12 |
| Context window | 400k | 262k |
| Parameters | — | 1T |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | MITOSI-approved |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex | Kimi K2.7-Code |
|---|---|---|
| Input price | $1.75/1M tokens | $0.95/1M tokens |
| Output price | $14/1M tokens | $4/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex | Kimi K2.7-Code |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | No | 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 | Yes | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on multimodal input: Kimi K2.7-Code and code execution: GPT-5.3-Codex. Both models share vision, reasoning mode, function calling, and tool use, 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-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Kimi K2.7-Code lists $0.95/1M input and $4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.7-Code lower by about $3.56 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose GPT-5.3-Codex 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, GPT-5.3-Codex or Kimi K2.7-Code?
GPT-5.3-Codex supports 400k 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GPT-5.3-Codex or Kimi K2.7-Code?
Kimi K2.7-Code is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Kimi K2.7-Code costs $0.95/1M input and $4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.3-Codex or Kimi K2.7-Code open source?
GPT-5.3-Codex 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-5.3-Codex or Kimi K2.7-Code?
Both GPT-5.3-Codex 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-5.3-Codex or Kimi K2.7-Code?
Kimi K2.7-Code has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Kimi K2.7-Code?
GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Kimi K2.7-Code is available on Moonshot AI Kimi. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.