Kimi K2 Thinking vs Qwen3-105B
Kimi K2 Thinking (2025) and Qwen3-105B (2025) are frontier reasoning models from Moonshot AI and Alibaba. Kimi K2 Thinking ships a 256k-token context window, while Qwen3-105B ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3-105B is safer overall; choose Kimi K2 Thinking when reasoning depth matters.
Decision scorecard
Local evidence first| Signal | Kimi K2 Thinking | Qwen3-105B |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | tool-calling agents |
| Decision fit | RAG, Long context, and Classification | RAG, Agents, and Long context |
| Context window | 256k | 128k |
| Cheapest output | $2.50/1M tokens | - |
| Provider routes | 7 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Kimi K2 Thinking has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2 Thinking has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2 Thinking uniquely exposes Reasoning and Structured outputs in local model data.
- Local decision data tags Kimi K2 Thinking for RAG, Long context, and Classification.
- Qwen3-105B uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Qwen3-105B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Kimi K2 Thinking
$1,105
Cheapest tracked route/tier: Fireworks AI
Qwen3-105B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Kimi K2 Thinking and Qwen3-105B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning and Structured outputs before moving production traffic.
- Qwen3-105B adds Function calling and Tool use in local capability data.
- No overlapping tracked provider route is sourced for Qwen3-105B and Kimi K2 Thinking; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Kimi K2 Thinking adds Reasoning and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2025-12-15 |
| Context window | 256k | 128k |
| Parameters | 1T (32B active) | 105B |
| Architecture | decoder only | - |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | - | 2025-02 |
Pricing and availability
| Pricing attribute | Kimi K2 Thinking | Qwen3-105B |
|---|---|---|
| Input price | $0.60/1M tokens | - |
| Output price | $2.50/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Kimi K2 Thinking | Qwen3-105B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Kimi K2 Thinking, function calling: Qwen3-105B, tool use: Qwen3-105B, and structured outputs: Kimi K2 Thinking. Both models share the core language-model surface, 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.
Pricing coverage is uneven: Kimi K2 Thinking has $0.60/1M input tokens and Qwen3-105B has no token price sourced yet. Provider availability is 7 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Kimi K2 Thinking when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Qwen3-105B when provider fit 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, Kimi K2 Thinking or Qwen3-105B?
Kimi K2 Thinking supports 256k tokens, while Qwen3-105B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Kimi K2 Thinking or Qwen3-105B open source?
Kimi K2 Thinking is listed under MIT. Qwen3-105B is listed under Apache 2.0. 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 reasoning mode, Kimi K2 Thinking or Qwen3-105B?
Kimi K2 Thinking has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, Kimi K2 Thinking or Qwen3-105B?
Qwen3-105B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Kimi K2 Thinking or Qwen3-105B?
Qwen3-105B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Kimi K2 Thinking and Qwen3-105B?
Kimi K2 Thinking is available on Fireworks AI, GCP Vertex AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Qwen3-105B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.