LLM Reference

GPT-5.1 Codex Max vs Kimi K2.6

GPT-5.1 Codex Max (2025) and Kimi K2.6 (2026) are agentic coding models from OpenAI and Moonshot AI. GPT-5.1 Codex Max ships a not-yet-sourced context window, while Kimi K2.6 ships a 262k-token context window. On pricing, Kimi K2.6 costs $0.73/1M input tokens versus $1.25/1M 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 K2.6 is ~71% cheaper at $0.73/1M; pay for GPT-5.1 Codex Max only for coding workflow support.

Decision scorecard

Local evidence first
SignalGPT-5.1 Codex MaxKimi K2.6
Best forcustom coding agents, code generation, and tool loopscustom coding agents, code generation, and tool loops
Decision fitCoding, Agents, and VisionCoding, RAG, and Agents
Context window262k
Cheapest output$10/1M tokens$3.49/1M tokens
Provider routes2 tracked9 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose GPT-5.1 Codex Max when...
  • Local decision data tags GPT-5.1 Codex Max for Coding, Agents, and Vision.
Choose Kimi K2.6 when...
  • Kimi K2.6 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Kimi K2.6 has the lower cheapest tracked output price at $3.49/1M tokens.
  • Kimi K2.6 has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Kimi K2.6 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 Kimi K2.6

GPT-5.1 Codex Max

$3,500

Cheapest tracked route/tier: OpenRouter

Kimi K2.6

$1,457

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $2,044. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.1 Codex Max -> Kimi K2.6
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Kimi K2.6 is $6.51/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Kimi K2.6 -> GPT-5.1 Codex Max
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • GPT-5.1 Codex Max is $6.51/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.

Specs

Specification
Released2025-11-192026-04-20
Context window262k
Parameters1T
Architecture-Mixture of Experts
LicenseProprietaryMIT(OSI)
OpennessProprietaryOpen source
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff2024-092025-04

Pricing and availability

Pricing attributeGPT-5.1 Codex MaxKimi K2.6
Input price$1.25/1M tokens$0.73/1M tokens
Output price$10/1M tokens$3.49/1M tokens
Providers

Capabilities

CapabilityGPT-5.1 Codex MaxKimi K2.6
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

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, GPT-5.1 Codex Max lists $1.25/1M input and $10/1M output tokens on the cheapest tracked provider, while Kimi K2.6 lists $0.73/1M input and $3.49/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.6 lower by about $2.32 per million blended tokens. Availability is 2 providers versus 9, so concentration risk also matters.

Choose GPT-5.1 Codex Max when coding workflow support are central to the workload. Choose Kimi K2.6 when coding workflow support, lower input-token cost, and broader provider choice 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 is cheaper, GPT-5.1 Codex Max or Kimi K2.6?

Kimi K2.6 is cheaper on tracked token pricing. GPT-5.1 Codex Max costs $1.25/1M input and $10/1M output tokens. Kimi K2.6 costs $0.73/1M input and $3.49/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.1 Codex Max or Kimi K2.6 open source?

GPT-5.1 Codex Max is listed under Proprietary. Kimi K2.6 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-5.1 Codex Max or Kimi K2.6?

Both GPT-5.1 Codex Max and Kimi K2.6 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-5.1 Codex Max or Kimi K2.6?

Both GPT-5.1 Codex Max and Kimi K2.6 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for reasoning mode, GPT-5.1 Codex Max or Kimi K2.6?

Both GPT-5.1 Codex Max and Kimi K2.6 expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run GPT-5.1 Codex Max and Kimi K2.6?

GPT-5.1 Codex Max is available on OpenRouter and Vercel AI Gateway. Kimi K2.6 is available on Cloudflare Workers AI, NVIDIA NIM, Moonshot AI Kimi, Fireworks AI, and OpenRouter. 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.