Claude Haiku 4.5 vs Kimi K2 Thinking Turbo
Claude Haiku 4.5 (2025) and Kimi K2 Thinking Turbo (2025) are general-purpose language models from Anthropic and Moonshot AI. Claude Haiku 4.5 ships a 200k-token context window, while Kimi K2 Thinking Turbo ships a 262k-token context window. On pricing, Claude Haiku 4.5 costs $0.80/1M input tokens versus $1.15/1M 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.
Claude Haiku 4.5 is ~44% cheaper at $0.80/1M; pay for Kimi K2 Thinking Turbo only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Claude Haiku 4.5 | Kimi K2 Thinking Turbo |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 200k | 262k |
| Cheapest output | $4/1M tokens | $8/1M tokens |
| Provider routes | 8 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Claude Haiku 4.5 has the lower cheapest tracked output price at $4/1M tokens.
- Claude Haiku 4.5 has broader tracked provider coverage for fallback and procurement flexibility.
- Claude Haiku 4.5 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Claude Haiku 4.5 for Coding, RAG, and Agents.
- Kimi K2 Thinking Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Kimi K2 Thinking Turbo for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Claude Haiku 4.5
$1,640
Cheapest tracked route/tier: AWS Bedrock
Kimi K2 Thinking Turbo
$2,920
Cheapest tracked route/tier: Vercel AI Gateway
Estimated monthly gap: $1,280. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Kimi K2 Thinking Turbo is $4/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Claude Haiku 4.5 is $4/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Claude Haiku 4.5 adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2025-11-06 |
| Context window | 200k | 262k |
| Parameters | — | 1T (32B active) |
| Architecture | decoder only | - |
| License | Proprietary | MIT(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-02 | - |
Pricing and availability
| Pricing attribute | Claude Haiku 4.5 | Kimi K2 Thinking Turbo |
|---|---|---|
| Input price | $0.80/1M tokens | $1.15/1M tokens |
| Output price | $4/1M tokens | $8/1M tokens |
| Providers |
Capabilities
| Capability | Claude Haiku 4.5 | Kimi K2 Thinking Turbo |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | 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 vision: Claude Haiku 4.5, multimodal input: Claude Haiku 4.5, function calling: Claude Haiku 4.5, tool use: Claude Haiku 4.5, structured outputs: Claude Haiku 4.5, and code execution: Claude Haiku 4.5. 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.
For cost, Claude Haiku 4.5 lists $0.80/1M input and $4/1M output tokens on the cheapest tracked provider, while Kimi K2 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Claude Haiku 4.5 lower by about $1.45 per million blended tokens. Availability is 8 providers versus 1, so concentration risk also matters.
Choose Claude Haiku 4.5 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Kimi K2 Thinking Turbo when long-context analysis 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, Claude Haiku 4.5 or Kimi K2 Thinking Turbo?
Kimi K2 Thinking Turbo supports 262k 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 Thinking Turbo?
Claude Haiku 4.5 is cheaper on tracked token pricing. Claude Haiku 4.5 costs $0.80/1M input and $4/1M output tokens. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Haiku 4.5 or Kimi K2 Thinking Turbo open source?
Claude Haiku 4.5 is listed under Proprietary. Kimi K2 Thinking Turbo 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 Thinking Turbo?
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 Thinking Turbo?
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 Thinking Turbo?
Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. Kimi K2 Thinking Turbo is available on Vercel AI Gateway. 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.