Pixtral Large (25.02) vs Phi-4-mini
Phi-4-mini comes out ahead, 58 to 33 on our weighted score, and it is the cheaper option too.
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
Add a model
Make it a three-way comparison.
Phi-4-mini is our pick
Phi-4-mini is the better all-round choice, scoring 58/100 against Pixtral Large (25.02) (33). It leads on price. Pixtral Large (25.02) wins on inputs & features. 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 pricePhi-4-miniPhi-4-mini $0.131 · Pixtral Large (25.02) $3.00 per 1M tokens (3:1 blend)
- Longest contextAbout the samePixtral Large (25.02) 128,000 · Phi-4-mini 128,000 tokens
- Widest inputsPixtral Large (25.02)Pixtral Large (25.02): Text, Images · Phi-4-mini: Text
- Self-hostingPhi-4-miniPublishes downloadable weights
| Measure | Weight | Pixtral Large (25.02) | Phi-4-mini |
|---|---|---|---|
| Price | 50% | 27 | 92 |
| Inputs & features | 30% | 50 | 25 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 33/100 | 58/100 |
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 | Pixtral Large (25.02)Mistral AI | Phi-4-miniMicrosoft |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $2.00 | $0.075 (best) |
| Output | $6.00 | $0.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.00 | $0.131 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Azure API |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | — | phi-4-mini |
| API providers | 3 (best) | 1 |
| Released | Apr 8, 2025 | Dec 11, 2024 |
| Knowledge cutoff | — | Oct 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Pixtral Large (25.02)$32.00
- Phi-4-mini$1.35
Which should you choose?
Which is better: Pixtral Large (25.02) or Phi-4-mini?
Phi-4-mini is the better all-round choice, scoring 58/100 against Pixtral Large (25.02) (33). It leads on price. Pixtral Large (25.02) wins on inputs & features. 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, Pixtral Large (25.02) or Phi-4-mini?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Pixtral Large (25.02) costs $2.00 input / $6.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $3.00 for Pixtral Large (25.02) (23× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Pixtral Large (25.02) has not been scored yet and Phi-4-mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Pixtral Large (25.02) and Phi-4-mini 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?
Pixtral Large (25.02) and Phi-4-mini share the same 128,000-token context window. Maximum output per response: Pixtral Large (25.02) up to 8,192, Phi-4-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Pixtral Large (25.02) accepts text and images; Phi-4-mini accepts text. Pixtral Large (25.02) handles the widest range of inputs.
Are any of these open source?
Phi-4-mini publishes its weights and can be self-hosted; Pixtral Large (25.02) is proprietary.
Which is newer?
Pixtral Large (25.02) is the newest, released Apr 8, 2025. Phi-4-mini came out Dec 11, 2024. Knowledge cutoff: Phi-4-mini Oct 2023.
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 Oct 4, 2026.
Related comparisons
- Add Qwen3-Coder 480B-A35B InstructThree-way comparison
- Pixtral Large (25.02) vs Qwen3-Coder 480B-A35B InstructAlibaba (Qwen)
- Pixtral Large (25.02) vs Sonar Deep ResearchPerplexity
- Pixtral Large (25.02) vs Jamba LargeAI21 Labs
- Pixtral Large (25.02) vs Command ACohere
- Phi-4-mini vs Nova LiteAmazon
- Phi-4-mini vs Llama-3.2-3BMeta
