gpt-oss-120b vs Kimi K2.6
gpt-oss-120b (2025) and Kimi K2.6 (2026) are agentic coding models from OpenAI and Moonshot AI. gpt-oss-120b ships a 131K-token context window, while Kimi K2.6 ships a 262K-token context window. On Google-Proof Q&A, Kimi K2.6 leads by 12.3 pts. On pricing, gpt-oss-120b costs $0.04/1M input tokens versus $0.75/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
gpt-oss-120b is ~1823% cheaper at $0.04/1M; pay for Kimi K2.6 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | gpt-oss-120b | Kimi K2.6 |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Coding, RAG, and Agents |
| Context window | 131K | 262K |
| Cheapest output | $0.18/1M tokens | $3.5/1M tokens |
| Provider routes | 7 tracked | 5 tracked |
| Shared benchmarks | 1 rows | Google-Proof Q&A leader |
Decision tradeoffs
- gpt-oss-120b has the lower cheapest tracked output price at $0.18/1M tokens.
- gpt-oss-120b has broader tracked provider coverage for fallback and procurement flexibility.
- gpt-oss-120b uniquely exposes Structured outputs in local model data.
- Local decision data tags gpt-oss-120b for RAG, Agents, and Long context.
- Kimi K2.6 leads the largest shared benchmark signal on Google-Proof Q&A by 12.3 points.
- Kimi K2.6 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.6 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- 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 prices on this page.
gpt-oss-120b
$76.20
Cheapest tracked route: OpenRouter
Kimi K2.6
$1,475
Cheapest tracked route: OpenRouter
Estimated monthly gap: $1,399. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on NVIDIA NIM, Fireworks AI, and OpenRouter; start route-level A/B tests there.
- Kimi K2.6 is $3.32/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Kimi K2.6 adds Vision, Multimodal, and Reasoning in local capability data.
- Provider overlap exists on OpenRouter, Fireworks AI, and NVIDIA NIM; start route-level A/B tests there.
- gpt-oss-120b is $3.32/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- gpt-oss-120b adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-05 | 2026-04-20 |
| Context window | 131K | 262K |
| Parameters | 120B | 1T |
| Architecture | decoder only | Mixture of Experts (MoE) |
| License | Open Source | Open Source |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | gpt-oss-120b | Kimi K2.6 |
|---|---|---|
| Input price | $0.04/1M tokens | $0.75/1M tokens |
| Output price | $0.18/1M tokens | $3.5/1M tokens |
| Providers |
Capabilities
| Capability | gpt-oss-120b | Kimi K2.6 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
| Benchmark | gpt-oss-120b | Kimi K2.6 |
|---|---|---|
| Google-Proof Q&A | 78.2 | 90.5 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has gpt-oss-120b at 78.2 and Kimi K2.6 at 90.5, with Kimi K2.6 ahead by 12.3 points. The largest visible gap is 12.3 points on Google-Proof Q&A, 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 vision: Kimi K2.6, multimodal input: Kimi K2.6, reasoning mode: Kimi K2.6, and structured outputs: gpt-oss-120b. Both models share 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-oss-120b lists $0.04/1M input and $0.18/1M output tokens, while Kimi K2.6 lists $0.75/1M input and $3.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts gpt-oss-120b lower by about $1.49 per million blended tokens. Availability is 7 providers versus 5, so concentration risk also matters.
Choose gpt-oss-120b when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Kimi K2.6 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, gpt-oss-120b or Kimi K2.6?
Kimi K2.6 supports 262K tokens, while gpt-oss-120b supports 131K 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-oss-120b or Kimi K2.6?
gpt-oss-120b is cheaper on tracked token pricing. gpt-oss-120b costs $0.04/1M input and $0.18/1M output tokens. Kimi K2.6 costs $0.75/1M input and $3.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is gpt-oss-120b or Kimi K2.6 open source?
gpt-oss-120b is listed under Open Source. Kimi K2.6 is listed under Open Source. 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-oss-120b or Kimi K2.6?
Kimi K2.6 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, gpt-oss-120b or Kimi K2.6?
Kimi K2.6 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-oss-120b and Kimi K2.6?
gpt-oss-120b is available on OpenRouter, Together AI, Fireworks AI, GCP Vertex AI, and NVIDIA NIM. Kimi K2.6 is available on NVIDIA NIM, Moonshot AI Kimi, Fireworks AI, OpenRouter, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.