ZMIME
Comparison · 2 models · Updated Nov 2, 2026

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

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

  1. 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

  2. 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

  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 inputsQwen3 VL 235B A22B Thinking: Text, Images · o4-mini-deep-research: Text, Images
  • Self-hostingQwen3 VL 235B A22B ThinkingPublishes downloadable weights
How the score is built
MeasureWeightQwen3 VL 235B A22B Thinkingo4-mini-deep-research
Price50%4225
Inputs & features30%6060
Context window20%2532
Overall100%44/10037/100

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.

Qwen3 VL 235B A22B Thinking vs o4-mini-deep-research specifications side by side
SpecificationQwen3 VL 235B A22B ThinkingAlibaba (Qwen)o4-mini-deep-researchOpenAI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.50 (best)$1.80
Output$3.95 (best)$7.20
Cached input——
Blended (3:1)$1.36 (best)$3.15
Long-context rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 1 providers
Limits
Context window131,072 tokens200,000 tokens (best)
Max output32,768 tokens100,000 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenProprietary
API model ID——
API providers5 (best)1
ReleasedSep 23, 2025Jun 26, 2025
Knowledge cutoffMar 31, 2025May 2024
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.

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

Which should you choose?

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

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

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. Qwen3 VL 235B A22B Thinking has not been scored yet and o4-mini-deep-research has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Thinking and o4-mini-deep-research 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: Qwen3 VL 235B A22B Thinking up to 32,768, o4-mini-deep-research up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3 VL 235B A22B Thinking accepts text and images; o4-mini-deep-research 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: Qwen3 VL 235B A22B Thinking Mar 31, 2025, o4-mini-deep-research May 2024.

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

Related comparisons