Codestral vs Phi-4-mini
Phi-4-mini comes out ahead, 58 to 48 on our weighted score, and it is the cheaper option too.
Mistral AICodestral
48/100- ECI—
- Price$0.30 / $0.90
- Context256K
- Our pick
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
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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 Codestral (48). It leads on price. Codestral 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 pricePhi-4-miniPhi-4-mini $0.131 · Codestral $0.45 per 1M tokens (3:1 blend)
- Longest contextCodestralCodestral 256,000 · Phi-4-mini 128,000 tokens
- Widest inputsSame inputsCodestral: Text · Phi-4-mini: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Codestral | Phi-4-mini |
|---|---|---|---|
| Price | 50% | 66 | 92 |
| Inputs & features | 30% | 25 | 25 |
| Context window | 20% | 36 | 24 |
| Overall | 100% | 48/100 | 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 | CodestralMistral AI | Phi-4-miniMicrosoft |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.30 | $0.075 (best) |
| Output | $0.90 | $0.30 (best) |
| Cached input | $0.03 | — |
| Blended (3:1) | $0.45 | $0.131 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Azure API |
| Limits | ||
| Context window | 256,000 tokens (best) | 128,000 tokens |
| Max output | 4,096 tokens | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | codestral-latest | phi-4-mini |
| API providers | 3 (best) | 1 |
| Released | May 29, 2024 | Dec 11, 2024 |
| Knowledge cutoff | Oct 2024 | 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.
- Codestral$4.80
- Phi-4-mini$1.35
Which should you choose?
Which is better: Codestral or Phi-4-mini?
Phi-4-mini is the better all-round choice, scoring 58/100 against Codestral (48). It leads on price. Codestral 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, Codestral or Phi-4-mini?
Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Codestral costs $0.30 input / $0.90 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 $0.45 for Codestral (3.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Codestral 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 Codestral 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?
Codestral has the largest context window at 256,000 tokens, against 128,000 for Phi-4-mini. Maximum output per response: Codestral up to 4,096, Phi-4-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Codestral accepts text; Phi-4-mini accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Phi-4-mini is the newest, released Dec 11, 2024. Codestral came out May 29, 2024. Knowledge cutoff: Codestral Oct 2024, 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.
