Claude Haiku 4.5 vs Kimi K2.5
Claude Haiku 4.5 (2025) and Kimi K2.5 (2026) are agentic coding models from Anthropic and Moonshot AI. Claude Haiku 4.5 ships a 200k-token context window, while Kimi K2.5 ships a 256K-token context window. On MultiChallenge, Kimi K2.5 leads by 10.9 pts. On pricing, Kimi K2.5 costs $0.44/1M input tokens versus $0.8/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Kimi K2.5 is ~82% cheaper at $0.44/1M; pay for Claude Haiku 4.5 only for coding workflow support.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2026-03-15 |
| Context window | 200k | 256K |
| Parameters | — | 1T (MoE, 384 experts) |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | MIT |
| Knowledge cutoff | 2025-02 | - |
Pricing and availability
| Pricing attribute | Claude Haiku 4.5 | Kimi K2.5 |
|---|---|---|
| Input price | $0.8/1M tokens | $0.44/1M tokens |
| Output price | $4/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Capability | Claude Haiku 4.5 | Kimi K2.5 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
| Benchmark | Claude Haiku 4.5 | Kimi K2.5 |
|---|---|---|
| MultiChallenge | 50.5 | 61.4 |
| BFCL | 68.7 | 68.3 |
Deep dive
On shared benchmark coverage, MultiChallenge has Claude Haiku 4.5 at 50.5 and Kimi K2.5 at 61.4, with Kimi K2.5 ahead by 10.9 points; BFCL has Claude Haiku 4.5 at 68.7 and Kimi K2.5 at 68.3, with Claude Haiku 4.5 ahead by 0.4 points. The largest visible gap is 10.9 points on MultiChallenge, 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: Claude Haiku 4.5, multimodal input: Claude Haiku 4.5, tool use: Claude Haiku 4.5, and code execution: Claude Haiku 4.5. Both models share function calling and structured outputs, 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, Claude Haiku 4.5 lists $0.8/1M input and $4/1M output tokens, while Kimi K2.5 lists $0.44/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.5 lower by about $0.85 per million blended tokens. Availability is 7 providers versus 7, so concentration risk also matters.
Choose Claude Haiku 4.5 when coding workflow support are central to the workload. Choose Kimi K2.5 when coding workflow support, larger context windows, 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.
FAQ
Which has a larger context window, Claude Haiku 4.5 or Kimi K2.5?
Kimi K2.5 supports 256K tokens, while Claude Haiku 4.5 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Claude Haiku 4.5 or Kimi K2.5?
Kimi K2.5 is cheaper on tracked token pricing. Claude Haiku 4.5 costs $0.8/1M input and $4/1M output tokens. Kimi K2.5 costs $0.44/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Haiku 4.5 or Kimi K2.5 open source?
Claude Haiku 4.5 is listed under Proprietary. Kimi K2.5 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, Claude Haiku 4.5 or Kimi K2.5?
Claude Haiku 4.5 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.
Which is better for multimodal input, Claude Haiku 4.5 or Kimi K2.5?
Claude Haiku 4.5 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 Claude Haiku 4.5 and Kimi K2.5?
Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. Kimi K2.5 is available on Fireworks AI, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.