Phi-4-mini vs Voxtral Small 24B 2507
Phi-4-mini comes out ahead, 58 to 55 on our weighted score, and it is the cheaper option too.
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
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 Voxtral Small 24B 2507 (55). It leads on price and context window. Voxtral Small 24B 2507 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 · Voxtral Small 24B 2507 $0.15 per 1M tokens (3:1 blend)
- Longest contextPhi-4-miniPhi-4-mini 128,000 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507Phi-4-mini: Text · Voxtral Small 24B 2507: Text, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Phi-4-mini | Voxtral Small 24B 2507 |
|---|---|---|---|
| Price | 50% | 92 | 89 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 24 | 0 |
| Overall | 100% | 58/100 | 55/100 |
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 | Phi-4-miniMicrosoft | Voxtral Small 24B 2507Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.075 (best) | $0.10 |
| Output | $0.30 | $0.30 |
| Cached input | — | — |
| Blended (3:1) | $0.131 (best) | $0.15 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Azure API | Official Mistral API |
| Limits | ||
| Context window | 128,000 tokens (best) | 32,768 tokens |
| Max output | 4,096 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache 2.0 |
| API model ID | phi-4-mini | voxtral-small-latest |
| API providers | 1 | 7 (best) |
| Released | Dec 11, 2024 | Jul 15, 2025 |
| 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.
- Phi-4-mini$1.35
- Voxtral Small 24B 2507$1.60
Which should you choose?
Which is better: Phi-4-mini or Voxtral Small 24B 2507?
Phi-4-mini is the better all-round choice, scoring 58/100 against Voxtral Small 24B 2507 (55). It leads on price and context window. Voxtral Small 24B 2507 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, Phi-4-mini or Voxtral Small 24B 2507?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Voxtral Small 24B 2507 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $0.15 for Voxtral Small 24B 2507 (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Phi-4-mini has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Phi-4-mini and Voxtral Small 24B 2507 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?
Phi-4-mini has the largest context window at 128,000 tokens, against 32,768 for Voxtral Small 24B 2507. Maximum output per response: Phi-4-mini up to 4,096, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Phi-4-mini accepts text; Voxtral Small 24B 2507 accepts text and audio. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Voxtral Small 24B 2507 is the newest, released Jul 15, 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.
