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Claude Haiku 4.5 vs Qwen3.5-235B-A22B-Instruct

Claude Haiku 4.5 (2025) and Qwen3.5-235B-A22B-Instruct (2026) are general-purpose language models from Anthropic and Alibaba. Claude Haiku 4.5 ships a 200k-token context window, while Qwen3.5-235B-A22B-Instruct ships a 512k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Qwen3.5-235B-A22B-Instruct is safer overall; choose Claude Haiku 4.5 when coding workflow support matters.

Specs

Released2025-10-012026-02-24
Context window200k512k
Parameters235B
Architecturedecoder onlyMoE
LicenseProprietaryApache 2.0
Knowledge cutoff2025-02-

Pricing and availability

Claude Haiku 4.5Qwen3.5-235B-A22B-Instruct
Input price$0.8/1M tokens-
Output price$4/1M tokens-
Providers-

Capabilities

Claude Haiku 4.5Qwen3.5-235B-A22B-Instruct
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

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.

Pricing coverage is uneven: Claude Haiku 4.5 has $0.8/1M input tokens and Qwen3.5-235B-A22B-Instruct has no token price sourced yet. Provider availability is 8 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Claude Haiku 4.5 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B-Instruct 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.

FAQ

Which has a larger context window, Claude Haiku 4.5 or Qwen3.5-235B-A22B-Instruct?

Qwen3.5-235B-A22B-Instruct supports 512k 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.

Is Claude Haiku 4.5 or Qwen3.5-235B-A22B-Instruct open source?

Claude Haiku 4.5 is listed under Proprietary. Qwen3.5-235B-A22B-Instruct 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 vision, Claude Haiku 4.5 or Qwen3.5-235B-A22B-Instruct?

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 Qwen3.5-235B-A22B-Instruct?

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.

Which is better for function calling, Claude Haiku 4.5 or Qwen3.5-235B-A22B-Instruct?

Claude Haiku 4.5 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.

Where can I run Claude Haiku 4.5 and Qwen3.5-235B-A22B-Instruct?

Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. Qwen3.5-235B-A22B-Instruct is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.