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o4-mini vs Qwen3-32B

A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.

Updated

o4-mini specs · Qwen3-32B specs
Verdict by category
  • Priceo4-mini

    o4-mini publishes pricing ($4.40 / 1M output tokens) while Qwen3-32B does not.

  • Context windowo4-mini

    o4-mini accepts 200K tokens vs 128K, 1.6× the room for long documents and codebases.

  • BenchmarksTie

    No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.

  • Modalitieso4-mini

    o4-mini supports 2 modalities (text, vision) vs 1 for Qwen3-32B.

  • OpennessQwen3-32B

    Qwen3-32B ships open weights (Apache-2.0); o4-mini is API-only.

On balance o4-mini edges ahead, winning 3 of 5 categories against Qwen3-32B's 1. o4-mini publishes pricing ($4.40 / 1M output tokens) while Qwen3-32B does not. o4-mini accepts 200K tokens vs 128K, 1.6× the room for long documents and codebases.

No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. They differ in modality coverage, o4-mini handles text, vision while Qwen3-32B handles text, which can be the deciding factor before you even look at benchmarks. Qwen3-32B ships open weights (Apache-2.0); o4-mini is API-only.

Both shipped within roughly a month of each other in 2025, so they share the same generation of training data and tooling. o4-mini is usually picked for reasoning and math workloads, while Qwen3-32B sees more deployments in open source llm and edge deployment. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.

Side-by-side specs

Speco4-miniQwen3-32B
ProviderOpenAIAlibaba
ReleasedApr 2025Apr 2025
Modalitiestext, visiontext
Context window200K tokens128K tokens
Max output,,
Input · 1M$1.10 / 1M tokensPricing not published
Output · 1M$4.40 / 1M tokensPricing not published
Knowledge cutoff2024-06,
Open weightsNoYes (Apache-2.0)
API availableYesYes

Pricing at scale

What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.

  • Light usage, 100k in / 50k out per day$9.90 vs ,
  • Heavy usage, 1M in / 500k out per day$99.00 vs ,
  • RAG workload, 5M in / 200k out per day$191 vs ,

Light usage, 100k in / 50k out per day: pricing not directly comparable (one or both models are missing public per-token rates). Heavy usage, 1M in / 500k out per day: pricing not directly comparable (one or both models are missing public per-token rates). RAG workload, 5M in / 200k out per day: pricing not directly comparable (one or both models are missing public per-token rates).

Price calculator

Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.

  • o4-mini$0.330
  • Qwen3-32BPricing unavailable

Benchmarks compared

Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.

o4-miniQwen3-32B
  • GPQA81.4
Pick o4-mini if

o4-mini fits when…

  • Strong reasoning at mid-tier price
  • Fast for a thinking model
  • Solid tool-use
  • Long-context tasks, handles 200K tokens vs 128K for Qwen3-32B.
  • Multimodal needs covering vision.
Pick Qwen3-32B if

Qwen3-32B fits when…

  • Apache-2.0
  • Fits modest hardware budgets
  • Self-hosting and on-prem requirements, open weights (Apache-2.0).
Don't want either?

Consider GPT-5.5

OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.

See GPT-5.5 specso4-mini vs GPT-5.5Qwen3-32B vs GPT-5.5

Frequently asked

  • Is o4-mini or Qwen3-32B cheaper?
    Per-token pricing isn't published for at least one of these models, check each model's spec page for current rates.
  • Which has the larger context window?
    o4-mini accepts 200K tokens vs 128K for Qwen3-32B.
  • Is o4-mini or Qwen3-32B better for coding?
    Both o4-mini and Qwen3-32B are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.
  • Are either of these models open source?
    Qwen3-32B ships open weights (Apache-2.0). o4-mini is API-only.
  • When were o4-mini and Qwen3-32B released?
    o4-mini was released by OpenAI on 2025-04-16. Qwen3-32B was released by Alibaba on 2025-04-29.
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