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Comparison · 2 models · Updated Nov 2, 2026

o4-mini-deep-research vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking comes out ahead, 44 to 37 on our weighted score, and it is the cheaper option too.

  1. OpenAI

    o4-mini-deep-research

    Released Jun 26, 2025

    37/100
    • ECI—
    • Price$1.80 / $7.20
    • Context200K
    Full specs Remove o4-mini-deep-research
  2. Our pick

    Alibaba (Qwen)

    Qwen3 VL 235B A22B Thinking

    Released Sep 23, 2025

    44/100
    • ECI—
    • Price$0.50 / $3.95
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 VL 235B A22B Thinking is our pick

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against o4-mini-deep-research (37). It leads on price. o4-mini-deep-research wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking $1.36 · o4-mini-deep-research $3.15 per 1M tokens (3:1 blend)
  • Longest contexto4-mini-deep-researcho4-mini-deep-research 200,000 · Qwen3 VL 235B A22B Thinking 131,072 tokens
  • Widest inputsSame inputso4-mini-deep-research: Text, Images · Qwen3 VL 235B A22B Thinking: Text, Images
  • Self-hostingQwen3 VL 235B A22B ThinkingPublishes downloadable weights
How the score is built
MeasureWeighto4-mini-deep-researchQwen3 VL 235B A22B Thinking
Price50%2542
Inputs & features30%6060
Context window20%3225
Overall100%37/10044/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

o4-mini-deep-research vs Qwen3 VL 235B A22B Thinking specifications side by side
Specificationo4-mini-deep-researchOpenAIQwen3 VL 235B A22B ThinkingAlibaba (Qwen)
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$1.80$0.50 (best)
Output$7.20$3.95 (best)
Cached input——
Blended (3:1)$3.15$1.36 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 5 providers
Limits
Context window200,000 tokens (best)131,072 tokens
Max output100,000 tokens (best)32,768 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsProprietaryOpen
API model ID——
API providers15 (best)
ReleasedJun 26, 2025Sep 23, 2025
Knowledge cutoffMay 2024Mar 31, 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • o4-mini-deep-research$32.40
  • Qwen3 VL 235B A22B Thinking$12.90
04 — Questions

Which should you choose?

Which is better: o4-mini-deep-research or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against o4-mini-deep-research (37). It leads on price. o4-mini-deep-research wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, o4-mini-deep-research or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking is cheaper at $0.50 input / $3.95 output per million tokens (median across 5 API providers). o4-mini-deep-research costs $1.80 input / $7.20 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $1.36 per million tokens for Qwen3 VL 235B A22B Thinking versus $3.15 for o4-mini-deep-research (2.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. o4-mini-deep-research has not been scored yet and Qwen3 VL 235B A22B Thinking has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for o4-mini-deep-research and Qwen3 VL 235B A22B Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

o4-mini-deep-research has the largest context window at 200,000 tokens, against 131,072 for Qwen3 VL 235B A22B Thinking. Maximum output per response: o4-mini-deep-research up to 100,000, Qwen3 VL 235B A22B Thinking up to 32,768 tokens.

Which can read images, PDFs, audio or video?

o4-mini-deep-research accepts text and images; Qwen3 VL 235B A22B Thinking accepts text and images. They handle the same number of input types.

Are any of these open source?

Qwen3 VL 235B A22B Thinking publishes its weights and can be self-hosted; o4-mini-deep-research is proprietary.

Which is newer?

Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. o4-mini-deep-research came out Jun 26, 2025. Knowledge cutoff: o4-mini-deep-research May 2024, Qwen3 VL 235B A22B Thinking Mar 31, 2025.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.

05 — Keep comparing

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