LLM Reference

Qwen2.5-72B-Instruct vs Qwen3.6-35B-A3B

Qwen2.5-72B-Instruct (2024) and Qwen3.6-35B-A3B (2026) compare a standalone API model against a coding-specialized model. Qwen2.5-72B-Instruct ships a 128k-token context window, while Qwen3.6-35B-A3B ships a 262k-token context window. On Google-Proof Q&A, Qwen3.6-35B-A3B leads by 47.6 pts. On pricing, Qwen3.6-35B-A3B costs $0.15/1M input tokens versus $0.18/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Qwen2.5-72B-Instruct is standalone API model, while Qwen3.6-35B-A3B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalQwen2.5-72B-InstructQwen3.6-35B-A3B
Product typeStandalone API modelCoding-specialized model
Best forprovider-routed productioncustom coding agents, code generation, and tool loops
Decision fitCoding, RAG, and Long contextCoding, RAG, and Agents
Context window128k262k
Cheapest output$0.54/1M tokens$1/1M tokens
Provider routes7 tracked2 tracked
Shared benchmarks1 rowsGoogle-Proof Q&A leader

Decision tradeoffs

Choose Qwen2.5-72B-Instruct when...
  • Qwen2.5-72B-Instruct has the lower cheapest tracked output price at $0.54/1M tokens.
  • Qwen2.5-72B-Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen2.5-72B-Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen2.5-72B-Instruct for Coding, RAG, and Long context.
Choose Qwen3.6-35B-A3B when...
  • Qwen3.6-35B-A3B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 47.6 points.
  • Qwen3.6-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.6-35B-A3B uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags Qwen3.6-35B-A3B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Qwen2.5-72B-Instruct

Qwen2.5-72B-Instruct

$279

Cheapest tracked route/tier: Chutes AI

Qwen3.6-35B-A3B

$370

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $91.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Qwen2.5-72B-Instruct -> Qwen3.6-35B-A3B
  • Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
  • Qwen3.6-35B-A3B is $0.46/1M 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.
  • Qwen3.6-35B-A3B adds Vision, Multimodal, and Function calling in local capability data.
Qwen3.6-35B-A3B -> Qwen2.5-72B-Instruct
  • Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
  • Qwen2.5-72B-Instruct is $0.46/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
  • Qwen2.5-72B-Instruct adds Structured outputs in local capability data.

Specs

Specification
Released2024-06-072026-04-16
Context window128k262k
Parameters72.7B35B
Architecturedecoder onlymoe
LicenseApache 2.0(OSI)Apache 2.0(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff--

Pricing and availability

Pricing attributeQwen2.5-72B-InstructQwen3.6-35B-A3B
Input price$0.18/1M tokens$0.15/1M tokens
Output price$0.54/1M tokens$1/1M tokens
Providers

Capabilities

CapabilityQwen2.5-72B-InstructQwen3.6-35B-A3B
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkQwen2.5-72B-InstructQwen3.6-35B-A3B
Google-Proof Q&A38.486.0

Deep dive

On shared benchmark coverage, Google-Proof Q&A has Qwen2.5-72B-Instruct at 38.4 and Qwen3.6-35B-A3B at 86, with Qwen3.6-35B-A3B ahead by 47.6 points. The largest visible gap is 47.6 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: Qwen3.6-35B-A3B, multimodal input: Qwen3.6-35B-A3B, function calling: Qwen3.6-35B-A3B, tool use: Qwen3.6-35B-A3B, and structured outputs: Qwen2.5-72B-Instruct. 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, Qwen2.5-72B-Instruct lists $0.18/1M input and $0.54/1M output tokens on the cheapest tracked provider, while Qwen3.6-35B-A3B lists $0.15/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $0.12 per million blended tokens. Availability is 7 providers versus 2, so concentration risk also matters.

Choose Qwen2.5-72B-Instruct when provider fit and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B 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, Qwen2.5-72B-Instruct or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B supports 262k tokens, while Qwen2.5-72B-Instruct supports 128k 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, Qwen2.5-72B-Instruct or Qwen3.6-35B-A3B?

Qwen2.5-72B-Instruct is cheaper on tracked token pricing. Qwen2.5-72B-Instruct costs $0.18/1M input and $0.54/1M output tokens. Qwen3.6-35B-A3B costs $0.15/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Qwen2.5-72B-Instruct or Qwen3.6-35B-A3B open source?

Qwen2.5-72B-Instruct is listed under Apache 2.0. Qwen3.6-35B-A3B 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, Qwen2.5-72B-Instruct or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B 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, Qwen2.5-72B-Instruct or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B 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 Qwen2.5-72B-Instruct and Qwen3.6-35B-A3B?

Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. Qwen3.6-35B-A3B is available on OpenRouter and Novita AI. 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.