Llama 4 Scout 17B Instruct vs Mistral Small 4 vs Mistral Small 3.1 24B
Llama 4 Scout 17B Instruct comes out ahead, 71 to 64 and 61 on our weighted score, though Mistral Small 4 is 23% cheaper per token.
- Our pick
MetaLlama 4 Scout 17B Instruct
71/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
Mistral AIMistral Small 4
64/100- ECI—
- Price$0.15 / $0.60
- Context256K
- Mistral AI
Mistral Small 3.1 24B
61/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
Llama 4 Scout 17B Instruct is our pick
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 71/100 against Mistral Small 4 (64) and Mistral Small 3.1 24B (61). It leads 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 priceMistral Small 4Mistral Small 4 $0.263 · Mistral Small 3.1 24B $0.281 · Llama 4 Scout 17B Instruct $0.341 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · Mistral Small 4 256,000 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsSame inputsLlama 4 Scout 17B Instruct: Text, Images · Mistral Small 4: Text, Images · Mistral Small 3.1 24B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama 4 Scout 17B Instruct | Mistral Small 4 | Mistral Small 3.1 24B |
|---|---|---|---|---|
| Price | 50% | 72 | 77 | 76 |
| Inputs & features | 30% | 50 | 60 | 60 |
| Context window | 20% | 100 | 36 | 24 |
| Overall | 100% | 71/100 | 64/100 | 61/100 |
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 | Llama 4 Scout 17B InstructMeta | Mistral Small 4Mistral AI | Mistral Small 3.1 24BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 129.7 (best) | — | 127.5 |
| ECI rank | #126 of 148 (best) | — | #132 of 148 |
| GPQA DiamondGraduate-level science questions | 51.8% (best) | — | 47.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% (best) | — | 5.8% |
| Price per million tokens | |||
| Input | $0.225 | $0.15 (best) | $0.229 |
| Output | $0.69 | $0.60 | $0.436 (best) |
| Cached input | — | $0.015 | — |
| Blended (3:1) | $0.341 | $0.263 (best) | $0.281 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Mistral API | Median of 2 providers |
| Limits | |||
| Context window | 10,000,000 tokens (best) | 256,000 tokens | 128,000 tokens |
| Max output | 16,384 tokens | 256,000 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yeshigh | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | mistral-small-2603 | — |
| API providers | 4 | 16 (best) | 2 |
| Released | Apr 5, 2025 | Mar 16, 2026 | Mar 17, 2025 |
| Knowledge cutoff | Aug 2024 | Jun 2025 | Jun 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama 4 Scout 17B Instruct$3.63
- Mistral Small 4$2.70
- Mistral Small 3.1 24B$3.16
Which should you choose?
Which is better: Llama 4 Scout 17B Instruct, Mistral Small 4 or Mistral Small 3.1 24B?
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 71/100 against Mistral Small 4 (64) and Mistral Small 3.1 24B (61). It leads 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, Llama 4 Scout 17B Instruct, Mistral Small 4 or Mistral Small 3.1 24B?
Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral API price). Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers); Llama 4 Scout 17B Instruct costs $0.225 input / $0.69 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for Mistral Small 4 versus $0.281 for Mistral Small 3.1 24B (1.1× as much) and $0.341 for Llama 4 Scout 17B Instruct (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama 4 Scout 17B Instruct has an ECI of 129.7, Mistral Small 4 has not been scored yet and Mistral Small 3.1 24B has an ECI of 127.5.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 4 Scout 17B Instruct, Mistral Small 4 and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 256,000 for Mistral Small 4 and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama 4 Scout 17B Instruct up to 16,384, Mistral Small 4 up to 256,000, Mistral Small 3.1 24B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Llama 4 Scout 17B Instruct accepts text and images; Mistral Small 4 accepts text and images; Mistral Small 3.1 24B accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Mistral Small 4 is the newest, released Mar 16, 2026. Llama 4 Scout 17B Instruct came out Apr 5, 2025; Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Llama 4 Scout 17B Instruct Aug 2024, Mistral Small 4 Jun 2025, Mistral Small 3.1 24B Jun 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 Oct 4, 2026.
