Model Comparison

Qwen3 32B vs Command A (Mar 25)

Compare the listed model data for Qwen3 32B by Qwen and Command A (Mar 25) by Cohere. Benchmark and pricing records are not a controlled test and may change.

Data last updated: 2026-10-16. Verify current model details with each provider.

What the listed data says

Qwen3 32B: 128K tokens; Command A (Mar 25): 256K tokens. Command A (Mar 25) has the larger listed context window. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; Command A (Mar 25) is listed for coding, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; Command A (Mar 25) 81.0%; HumanEval: Qwen3 32B 92.7%; Command A (Mar 25) 78.4%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.

Computed differences from catalog data

  • The listed context windows are 128K tokens and 256K tokens; the larger is 2× the smaller.
  • On shared numeric benchmark entries, MMLU: Qwen3 32B − Command A (Mar 25) = +11 percentage points (92.0% vs 81.0%); HumanEval: Qwen3 32B − Command A (Mar 25) = +14.3 percentage points (92.7% vs 78.4%).
  • The first listed parameter quantities are 32B and 111B; the larger quantity is 3.47× the smaller. Total and active MoE parameters are not directly equivalent.
  • The catalog release dates are April 2025 and March 2025, about 1 month apart at the precision supplied.

Cost example: 1M input and 1M output tokens

Using only the catalog's listed per-million-token rates, 1M input plus 1M output tokens costs about $1 for Qwen3 32B and $0.75 for Command A (Mar 25). This excludes provider-specific discounts, caching, and other fees.

Choose Qwen3 32B if…

Choose Qwen3 32B when your task aligns with catalog-listed uses or strengths such as Production coding assistants for enterprise software teams, Mathematical reasoning and data science, Complex document analysis and long-form reporting, Multilingual enterprise applications.

Choose Command A (Mar 25) if…

Choose Command A (Mar 25) when your task aligns with catalog-listed uses or strengths such as Enterprise search and RAG deployments, Multi-step business process automation, Legal, financial, medical document analysis in 23 languages, Cohere's flagship enterprise model for RAG and tool-use workflows.

Qwen3 32B

Browse Qwen models

32B dense Qwen3 — excels at complex coding, mathematics, and deep multi-step reasoning. Top performer in its size class.

Parameters: 32B

Context: 128K tokens

Catalog pricing: Open source — free. Third-party API ~$0.14-0.30/MTok

Qwen Coding · Reasoning · Agentic · Long Context Open Source

View Qwen3 32B model profile

Command A (Mar 25)

Browse Cohere models

Cohere's enterprise flagship — 111B params, 256k context. Elite for long documents, agentic tasks, and enterprise RAG.

Parameters: 111B

Context: 256K tokens

Catalog pricing: Cohere API: $2.50/MTok input, $10.00/MTok output

Cohere Coding · Agentic · Long Context

View Command A (Mar 25) model profile

Feature Comparison — Qwen3 32B vs Command A (Mar 25)

Catalog specifications for Qwen3 32B and Command A (Mar 25)
Specification Qwen3 32B Command A (Mar 25)
Provider Qwen Cohere
Parameters 32B 111B
Context window 128K tokens 256K tokens
Maximum output Not listed Not listed
Catalog pricing Open source — free. Third-party API ~$0.14-0.30/MTok Cohere API: $2.50/MTok input, $10.00/MTok output
Listed input/output cost per 1M tokens input $0.3, output $0.7 per 1M tokens input $0.15, output $0.6 per 1M tokens
License Apache 2.0 CC BY-NC 4.0 for research; commercial requires API agreement
Coding support Listed Listed
Reasoning support Listed Not listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes No
Benchmark: MMLU 92.0% 81.0%
Benchmark: HumanEval 92.7% 78.4%

Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.

Frequently Asked Questions

What is different between Qwen3 32B and Command A (Mar 25)?
Qwen3 32B: 128K tokens; Command A (Mar 25): 256K tokens. Command A (Mar 25) has the larger listed context window. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; Command A (Mar 25) is listed for coding, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; Command A (Mar 25) 81.0%; HumanEval: Qwen3 32B 92.7%; Command A (Mar 25) 78.4%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Qwen3 32B and Command A (Mar 25)?
MMLU: Qwen3 32B 92.0%; Command A (Mar 25) 81.0%; HumanEval: Qwen3 32B 92.7%; Command A (Mar 25) 78.4%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Qwen3 32B: 128K tokens; Command A (Mar 25): 256K tokens. Command A (Mar 25) has the larger listed context window.
What are the listed costs per million tokens for Qwen3 32B and Command A (Mar 25)?
Qwen3 32B: input $0.3, output $0.7 per 1M tokens (Open source — free. Third-party API ~$0.14-0.30/MTok). Command A (Mar 25): input $0.15, output $0.6 per 1M tokens (Cohere API: $2.50/MTok input, $10.00/MTok output). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Qwen3 32B and Command A (Mar 25)?
The catalog lists Qwen3 32B as April 2025 and Command A (Mar 25) as March 2025, about 1 month apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Qwen3 32B and Command A (Mar 25)?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.

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