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MiniMax M2.7 vs Qwen3.5-27B

MiniMax M2.7 (2026) and Qwen3.5-27B (2026) are frontier-tier reasoning models from MiniMax and Alibaba. MiniMax M2.7 ships a 205K-token context window, while Qwen3.5-27B ships a 262K-token context window. On Google-Proof Q&A, MiniMax M2.7 leads by 1.6 pts. On pricing, Qwen3.5-27B costs $0.2/1M input tokens versus $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Qwen3.5-27B is ~54% cheaper at $0.2/1M; pay for MiniMax M2.7 only for provider fit.

Decision scorecard

Local evidence first
SignalMiniMax M2.7Qwen3.5-27B
Decision fitRAG, Agents, and Long contextRAG, Agents, and Long context
Context window205K262K
Cheapest output$1.2/1M tokens$1.56/1M tokens
Provider routes2 tracked3 tracked
Shared benchmarksGoogle-Proof Q&A leader1 rows

Decision tradeoffs

Choose MiniMax M2.7 when...
  • MiniMax M2.7 leads the largest shared benchmark signal on Google-Proof Q&A by 1.6 points.
  • MiniMax M2.7 has the lower cheapest tracked output price at $1.2/1M tokens.
  • Local decision data tags MiniMax M2.7 for RAG, Agents, and Long context.
Choose Qwen3.5-27B when...
  • Qwen3.5-27B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-27B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.5-27B uniquely exposes Vision and Multimodal in local model data.
  • Local decision data tags Qwen3.5-27B for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate MiniMax M2.7

MiniMax M2.7

$540

Cheapest tracked route: OpenRouter

Qwen3.5-27B

$546

Cheapest tracked route: OpenRouter

Estimated monthly gap: $6.00. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

MiniMax M2.7 -> Qwen3.5-27B
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Qwen3.5-27B is $0.36/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Qwen3.5-27B adds Vision and Multimodal in local capability data.
Qwen3.5-27B -> MiniMax M2.7
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • MiniMax M2.7 is $0.36/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision and Multimodal before moving production traffic.

Specs

Specification
Released2026-03-182026-02-24
Context window205K262K
Parameters10B active27B
Architecturedecoder onlydecoder only
LicenseProprietaryApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeMiniMax M2.7Qwen3.5-27B
Input price$0.3/1M tokens$0.2/1M tokens
Output price$1.2/1M tokens$1.56/1M tokens
Providers

Capabilities

CapabilityMiniMax M2.7Qwen3.5-27B
VisionNoYes
MultimodalNoYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionNoNo

Benchmarks

BenchmarkMiniMax M2.7Qwen3.5-27B
Google-Proof Q&A87.485.8

Deep dive

On shared benchmark coverage, Google-Proof Q&A has MiniMax M2.7 at 87.4 and Qwen3.5-27B at 85.8, with MiniMax M2.7 ahead by 1.6 points. The largest visible gap is 1.6 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: Qwen3.5-27B and multimodal input: Qwen3.5-27B. Both models share reasoning mode, function calling, tool use, 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, MiniMax M2.7 lists $0.3/1M input and $1.2/1M output tokens, while Qwen3.5-27B lists $0.2/1M input and $1.56/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts MiniMax M2.7 lower by about $0.03 per million blended tokens. Availability is 2 providers versus 3, so concentration risk also matters.

Choose MiniMax M2.7 when provider fit are central to the workload. Choose Qwen3.5-27B when long-context analysis, 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, MiniMax M2.7 or Qwen3.5-27B?

Qwen3.5-27B supports 262K tokens, while MiniMax M2.7 supports 205K 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, MiniMax M2.7 or Qwen3.5-27B?

Qwen3.5-27B is cheaper on tracked token pricing. MiniMax M2.7 costs $0.3/1M input and $1.2/1M output tokens. Qwen3.5-27B costs $0.2/1M input and $1.56/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is MiniMax M2.7 or Qwen3.5-27B open source?

MiniMax M2.7 is listed under Proprietary. Qwen3.5-27B 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, MiniMax M2.7 or Qwen3.5-27B?

Qwen3.5-27B 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, MiniMax M2.7 or Qwen3.5-27B?

Qwen3.5-27B 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 MiniMax M2.7 and Qwen3.5-27B?

MiniMax M2.7 is available on OpenRouter and Fireworks AI. Qwen3.5-27B is available on DeepInfra, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.