LLM Reference

GPT-5.1 vs Kimi K2.6

GPT-5.1 (2025) and Kimi K2.6 (2026) compare a standalone API model against a coding-specialized model. GPT-5.1 ships a 262k-token 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 page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: GPT-5.1 is standalone API model, while Kimi K2.6 is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalGPT-5.1Kimi K2.6
Product typeStandalone API modelCoding-specialized model
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentscustom coding agents, code generation, and tool loops
Decision fitRAG, Agents, and Long contextCoding, RAG, and Agents
Context window262k262k
Cheapest output$10/1M tokens$3.49/1M tokens
Provider routes1 tracked8 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.1 when...
  • Local decision data tags GPT-5.1 for RAG, Agents, and Long context.
Choose Kimi K2.6 when...
  • 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

$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 -> Kimi K2.6
  • Provider overlap exists on OpenRouter; 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
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-5.1 is $6.51/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.

Specs

Specification
Released2025-11-132026-04-20
Context window262k262k
Parameters1T
Architecture-Mixture of Experts (MoE)
LicenseProprietaryMIT(OSI)
OpennessProprietaryOpen source
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff-2025-04

Pricing and availability

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

Capabilities

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

Benchmarks

No shared benchmark rows are currently sourced 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 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 1 providers versus 8, so concentration risk also matters.

Choose GPT-5.1 when vision-heavy evaluation 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 has a larger context window, GPT-5.1 or Kimi K2.6?

GPT-5.1 supports 262k tokens, while Kimi K2.6 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-5.1 or Kimi K2.6?

Kimi K2.6 is cheaper on tracked token pricing. GPT-5.1 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 or Kimi K2.6 open source?

GPT-5.1 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 or Kimi K2.6?

Both GPT-5.1 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 or Kimi K2.6?

Both GPT-5.1 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

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

GPT-5.1 is available on OpenRouter. 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: 2026-06-04. Data sourced from public model cards and provider documentation.