Mistral Small 3.1 24B vs DeepSeek V3 0324 vs Llama 4 Scout 17B Instruct
Llama 4 Scout 17B Instruct comes out ahead, 62 to 55 and 54 on our weighted score, though Mistral Small 3.1 24B is 18% cheaper per token.
Mistral AI
Mistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
DeepSeek
DeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
- Our pick
Meta
Llama 4 Scout 17B Instruct
62/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
Llama 4 Scout 17B Instruct is our pick
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Small 3.1 24B (55) and DeepSeek V3 0324 (54). It leads on context window. Mistral Small 3.1 24B wins on price and inputs & features. DeepSeek V3 0324 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V3 0324Capabilities Index (ECI): DeepSeek V3 0324 135.9 · Llama 4 Scout 17B Instruct 129.7 · Mistral Small 3.1 24B 127.5
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Llama 4 Scout 17B Instruct $0.341 · DeepSeek V3 0324 $0.405 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · DeepSeek V3 0324 163,840 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24B and Llama 4 Scout 17B InstructMistral Small 3.1 24B: Text, Images · DeepSeek V3 0324: Text · Llama 4 Scout 17B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Small 3.1 24B | DeepSeek V3 0324 | Llama 4 Scout 17B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 50 | 60 | 52 |
| Price | 25% | 76 | 68 | 72 |
| Inputs & features | 15% | 60 | 25 | 50 |
| Context window | 10% | 24 | 28 | 100 |
| Overall | 100% | 55/100 | 54/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.5 | 135.9 (best) | 129.7 |
| ECI rank | #132 of 148 | #114 of 148 (best) | #126 of 148 |
| GPQA DiamondGraduate-level science questions | 47.5% | 67.6% (best) | 51.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 5.8% | 37.8% (best) | 7.8% |
| Price per million tokens | |||
| Input | $0.229 | $0.24 | $0.225 (best) |
| Output | $0.436 (best) | $0.90 | $0.69 |
| Cached input | — | — | — |
| Blended (3:1) | $0.281 (best) | $0.405 | $0.341 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 5 providers | Median of 4 providers |
| Limits | |||
| Context window | 128,000 tokens | 163,840 tokens | 10,000,000 tokens (best) |
| Max output | 16,384 tokens | 163,840 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | — |
| API providers | 2 | 5 (best) | 4 |
| Released | Mar 17, 2025 | Mar 24, 2025 | Apr 5, 2025 |
| Knowledge cutoff | Jun 2024 | — | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Mistral Small 3.1 24B$3.16
DeepSeek V3 0324$4.20
Llama 4 Scout 17B Instruct$3.63
Which should you choose?
Which is better: Mistral Small 3.1 24B, DeepSeek V3 0324 or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Small 3.1 24B (55) and DeepSeek V3 0324 (54). It leads on context window. Mistral Small 3.1 24B wins on price and inputs & features. DeepSeek V3 0324 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Small 3.1 24B, DeepSeek V3 0324 or Llama 4 Scout 17B Instruct?
Mistral Small 3.1 24B is cheaper at $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); DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $0.341 for Llama 4 Scout 17B Instruct (1.2× as much) and $0.405 for DeepSeek V3 0324 (1.4× as much).
Which scores higher on benchmarks?
DeepSeek V3 0324 scores higher on the Capabilities Index (ECI): DeepSeek V3 0324 135.9 (#114 of 148), Llama 4 Scout 17B Instruct 129.7 (#126 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). Their confidence ranges do not overlap (132.4–138.0 vs 124.8–131.4), so the gap is a real one. On individual benchmarks: GPQA Diamond — DeepSeek V3 0324 67.6%, Llama 4 Scout 17B Instruct 51.8%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — DeepSeek V3 0324 37.8%, Llama 4 Scout 17B Instruct 7.8%, Mistral Small 3.1 24B 5.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 3.1 24B, DeepSeek V3 0324 and Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, DeepSeek V3 0324 leads, which tends to carry over to coding, but test on your own codebase. 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 163,840 for DeepSeek V3 0324 and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Mistral Small 3.1 24B up to 16,384, DeepSeek V3 0324 up to 163,840, Llama 4 Scout 17B Instruct up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 3.1 24B accepts text and images; DeepSeek V3 0324 accepts text; Llama 4 Scout 17B Instruct accepts text and images. Mistral Small 3.1 24B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Llama 4 Scout 17B Instruct is the newest, released Apr 5, 2025. DeepSeek V3 0324 came out Mar 24, 2025; Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Mistral Small 3.1 24B Jun 2024, Llama 4 Scout 17B Instruct Aug 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.