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o4-mini vs Qwen3-72B

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 · Qwen3-72B specs
Verdict by category
  • Priceo4-mini

    o4-mini publishes pricing ($4.40 / 1M output tokens) while Qwen3-72B 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 Qwen3-72B.

  • OpennessQwen3-72B

    Qwen3-72B ships open weights (Apache-2.0); o4-mini is API-only.

On balance o4-mini edges ahead, winning 3 of 5 categories against Qwen3-72B's 1. o4-mini publishes pricing ($4.40 / 1M output tokens) while Qwen3-72B 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 Qwen3-72B handles text, which can be the deciding factor before you even look at benchmarks. Qwen3-72B 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 Qwen3-72B sees more deployments in open source llm and commercial use llm. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.

Side-by-side specs

Speco4-miniQwen3-72B
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
  • Qwen3-72BPricing 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-miniQwen3-72B
  • MMLU,84.0
  • 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 Qwen3-72B.
  • Multimodal needs covering vision.
Pick Qwen3-72B if

Qwen3-72B fits when…

  • Apache-2.0 license
  • Strongest open-weight on Chinese
  • Strong multilingual coverage
  • 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-5.5Qwen3-72B vs GPT-5.5

Frequently asked

  • Is o4-mini or Qwen3-72B 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 Qwen3-72B.
  • Is o4-mini or Qwen3-72B better for coding?
    Both o4-mini and Qwen3-72B 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?
    Qwen3-72B ships open weights (Apache-2.0). o4-mini is API-only.
  • When were o4-mini and Qwen3-72B released?
    o4-mini was released by OpenAI on 2025-04-16. Qwen3-72B was released by Alibaba on 2025-04-29.
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