o4-mini-deep-research vs Pixtral Large (25.02)
o4-mini-deep-research comes out ahead, 37 to 33 on our weighted score.
- Our pick
OpenAIo4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
Add a model
Make it a three-way comparison.
o4-mini-deep-research is our pick
o4-mini-deep-research is the better all-round choice, scoring 37/100 against Pixtral Large (25.02) (33). It leads on inputs & features and 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 pricePixtral Large (25.02)Pixtral Large (25.02) $3.00 · o4-mini-deep-research $3.15 per 1M tokens (3:1 blend)
- Longest contexto4-mini-deep-researcho4-mini-deep-research 200,000 · Pixtral Large (25.02) 128,000 tokens
- Widest inputsSame inputso4-mini-deep-research: Text, Images · Pixtral Large (25.02): Text, Images
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | o4-mini-deep-research | Pixtral Large (25.02) |
|---|---|---|---|
| Price | 50% | 25 | 26 |
| Inputs & features | 30% | 60 | 50 |
| Context window | 20% | 32 | 24 |
| Overall | 100% | 37/100 | 33/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o4-mini-deep-researchOpenAI | Pixtral Large (25.02)Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $1.80 (best) | $2.00 |
| Output | $7.20 | $6.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.15 | $3.00 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 3 providers |
| Limits | ||
| Context window | 200,000 tokens (best) | 128,000 tokens |
| Max output | 100,000 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | — |
| API providers | 1 | 3 (best) |
| Released | Jun 26, 2025 | Apr 8, 2025 |
| Knowledge cutoff | May 2024 | — |
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
- Pixtral Large (25.02)$32.00
Which should you choose?
Which is better: o4-mini-deep-research or Pixtral Large (25.02)?
o4-mini-deep-research is the better all-round choice, scoring 37/100 against Pixtral Large (25.02) (33). It leads on inputs & features and 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 Pixtral Large (25.02)?
Pixtral Large (25.02) is cheaper at $2.00 input / $6.00 output per million tokens (median across 3 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 $3.00 per million tokens for Pixtral Large (25.02) versus $3.15 for o4-mini-deep-research (1.1× 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 Pixtral Large (25.02) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini-deep-research and Pixtral Large (25.02) 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 128,000 for Pixtral Large (25.02). Maximum output per response: o4-mini-deep-research up to 100,000, Pixtral Large (25.02) up to 8,192 tokens.
Which can read images, PDFs, audio or video?
o4-mini-deep-research accepts text and images; Pixtral Large (25.02) accepts text and images. They handle the same number of input types.
Are any of these open source?
No. o4-mini-deep-research and Pixtral Large (25.02) are proprietary and only available through APIs and apps.
Which is newer?
o4-mini-deep-research is the newest, released Jun 26, 2025. Pixtral Large (25.02) came out Apr 8, 2025. Knowledge cutoff: 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.
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