LLM Reference

Command A vs Qwen3.5-9B

Command A (2025) and Qwen3.5-9B (2026) are general-purpose language models from Cohere and Alibaba. Command A ships a 256k-token context window, while Qwen3.5-9B ships a 262K-token context window. On MMLU PRO, Qwen3.5-9B leads by 11.3 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $2.50/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Qwen3.5-9B is ~2400% cheaper at $0.10/1M; pay for Command A only for provider fit.

Decision scorecard

Local evidence first
SignalCommand AQwen3.5-9B
Best forprovider-routed productionmultimodal apps, tool-calling agents, and provider-routed production
Decision fitLong context and ClassificationRAG, Agents, and Long context
Context window256k262K
Cheapest output$10/1M tokens$0.15/1M tokens
Provider routes2 tracked3 tracked
Shared benchmarks2 rowsMMLU PRO leader

Decision tradeoffs

Choose Command A when...
  • Local decision data tags Command A for Long context and Classification.
Choose Qwen3.5-9B when...
  • Qwen3.5-9B leads the largest shared benchmark signal on MMLU PRO by 11.3 points.
  • Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
  • Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.

Monthly cost at traffic

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

Lower estimate Qwen3.5-9B

Command A

$4,500

Cheapest tracked route/tier: OpenRouter

Qwen3.5-9B

$118

Cheapest tracked route/tier: Together AI

Estimated monthly gap: $4,383. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Command A -> Qwen3.5-9B
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Qwen3.5-9B is $9.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
Qwen3.5-9B -> Command A
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Command A is $9.85/1M 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.

Specs

Specification
Released2025-03-242026-03-02
Context window256k262K
Parameters111B9B
Architecture-decoder only
LicenseProprietaryApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeCommand AQwen3.5-9B
Input price$2.50/1M tokens$0.10/1M tokens
Output price$10/1M tokens$0.15/1M tokens
Providers

Capabilities

CapabilityCommand AQwen3.5-9B
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkCommand AQwen3.5-9B
MMLU PRO71.282.5
Google-Proof Q&A52.781.7

Deep dive

On shared benchmark coverage, MMLU PRO has Command A at 71.2 and Qwen3.5-9B at 82.5, with Qwen3.5-9B ahead by 11.3 points; Google-Proof Q&A has Command A at 52.7 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 29 points. The largest visible gap is 29 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: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, tool use: Qwen3.5-9B, and structured outputs: Qwen3.5-9B. 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, Command A lists $2.50/1M input and $10/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $4.63 per million blended tokens. Availability is 2 providers versus 3, so concentration risk also matters.

Choose Command A when provider fit are central to the workload. Choose Qwen3.5-9B 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, Command A or Qwen3.5-9B?

Qwen3.5-9B supports 262K tokens, while Command A supports 256k 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, Command A or Qwen3.5-9B?

Qwen3.5-9B is cheaper on tracked token pricing. Command A costs $2.50/1M input and $10/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Command A or Qwen3.5-9B open source?

Command A is listed under Proprietary. Qwen3.5-9B 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, Command A or Qwen3.5-9B?

Qwen3.5-9B 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, Command A or Qwen3.5-9B?

Qwen3.5-9B 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 Command A and Qwen3.5-9B?

Command A is available on OpenRouter and Vercel AI Gateway. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.