LLM Reference

Qwen3.5-27B vs Qwen3.6-27B

Qwen3.5-27B (2026) and Qwen3.6-27B (2026) compare a standalone API model against a coding-specialized model. Qwen3.5-27B ships a 262k-token context window, while Qwen3.6-27B ships a 262k-token context window. On MMLU PRO, Qwen3.6-27B leads by 0.1 pts. On pricing, Qwen3.5-27B costs $0.20/1M input tokens versus $0.32/1M 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: Qwen3.5-27B is standalone API model, while Qwen3.6-27B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalQwen3.5-27BQwen3.6-27B
Product typeStandalone API modelCoding-specialized model
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentscustom coding agents, code generation, and tool loops
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window262k262k
Cheapest output$1.56/1M tokens$3.20/1M tokens
Provider routes4 tracked4 tracked
Shared benchmarks6 sharedMMLU PRO leader

Decision tradeoffs

Choose Qwen3.5-27B when...
  • Qwen3.5-27B holds a shared-benchmark lead on Humanity's Last Exam, ahead by 0.3 points.
  • Qwen3.5-27B has the lower cheapest tracked output price at $1.56/1M tokens.
  • Qwen3.5-27B uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen3.5-27B for Coding, RAG, and Agents.
Choose Qwen3.6-27B when...
  • Qwen3.6-27B holds a shared-benchmark lead on MMLU PRO, ahead by 0.1 points.
  • Local decision data tags Qwen3.6-27B 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 Qwen3.5-27B

Qwen3.5-27B

$546

Cheapest tracked route/tier: OpenRouter

Qwen3.6-27B

$1,056

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $510. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Qwen3.5-27B -> Qwen3.6-27B
  • Provider overlap exists on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI; start route-level A/B tests there.
  • Qwen3.6-27B is $1.64/1M 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.
Qwen3.6-27B -> Qwen3.5-27B
  • Provider overlap exists on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI; start route-level A/B tests there.
  • Qwen3.5-27B is $1.64/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Qwen3.5-27B adds Structured outputs in local capability data.

Specs

Specification
Released2026-02-242026-04-27
Context window262k262k
Parameters27B27B
ArchitectureDecoder OnlyDecoder Only
LicenseApache 2.0OSI-approvedApache 2.0OSI-approved
OpennessOpen sourceOpen source
WeightsAvailableAvailable
CodeUnknownUnknown
Commercial useCommercial use: permittedCommercial use: permitted
Knowledge cutoff--

Pricing and availability

Pricing attributeQwen3.5-27BQwen3.6-27B
Input price$0.20/1M tokens$0.32/1M tokens
Output price$1.56/1M tokens$3.20/1M tokens
Providers

Capabilities

CapabilityQwen3.5-27BQwen3.6-27B
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkQwen3.5-27BQwen3.6-27B
MMLU PRO86.186.2
SWE-bench Verified72.477.2
Google-Proof Q&A85.887.8
LiveCodeBench80.783.9
Humanity's Last Exam24.324.0
MMMU Pro75.075.8

Deep dive

On shared benchmark coverage, MMLU PRO has Qwen3.5-27B at 86.1 and Qwen3.6-27B at 86.2, with Qwen3.6-27B ahead by 0.1 points; SWE-bench Verified has Qwen3.5-27B at 72.4 and Qwen3.6-27B at 77.2, with Qwen3.6-27B ahead by 4.8 points; Google-Proof Q&A has Qwen3.5-27B at 85.8 and Qwen3.6-27B at 87.8, with Qwen3.6-27B ahead by 2 points. The largest visible gap is 4.8 points on SWE-bench Verified, 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 structured outputs: Qwen3.5-27B. Both models share vision, multimodal input, reasoning mode, and function calling, 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, Qwen3.5-27B lists $0.20/1M input and $1.56/1M output tokens on the cheapest tracked provider, while Qwen3.6-27B lists $0.32/1M input and $3.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-27B lower by about $0.58 per million blended tokens. Availability is 4 providers versus 4, so concentration risk also matters.

Choose Qwen3.5-27B when vision-heavy evaluation and lower input-token cost are central to the workload. Choose Qwen3.6-27B when coding workflow support 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, Qwen3.5-27B or Qwen3.6-27B?

Qwen3.5-27B supports 262k tokens, while Qwen3.6-27B supports 262k 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, Qwen3.5-27B or Qwen3.6-27B?

Qwen3.5-27B is cheaper on tracked token pricing. Qwen3.5-27B costs $0.20/1M input and $1.56/1M output tokens. Qwen3.6-27B costs $0.32/1M input and $3.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Qwen3.5-27B or Qwen3.6-27B open source?

Qwen3.5-27B is listed under Apache 2.0. Qwen3.6-27B 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, Qwen3.5-27B or Qwen3.6-27B?

Both Qwen3.5-27B and Qwen3.6-27B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Qwen3.5-27B or Qwen3.6-27B?

Both Qwen3.5-27B and Qwen3.6-27B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run Qwen3.5-27B and Qwen3.6-27B?

Qwen3.5-27B is available on DeepInfra, OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. Qwen3.6-27B is available on OpenRouter, Alibaba Cloud PAI-EAS, Vercel AI Gateway, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.