Mistral Small 4 vs Llama 4 Scout 17B Instruct vs Hy3 preview
Llama 4 Scout 17B Instruct comes out ahead, 71 to 64 and 56 on our weighted score, though Mistral Small 4 is 23% cheaper per token.
Mistral AIMistral Small 4
64/100- ECI—
- Price$0.15 / $0.60
- Context256K
- Our pick
MetaLlama 4 Scout 17B Instruct
71/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
TencentHy3 preview
56/100- ECI—
- Price$0.176 / $0.586
- Context256K
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 Hy3 preview (56). It leads on context window. Mistral Small 4 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 priceMistral Small 4Mistral Small 4 $0.263 · Hy3 preview $0.279 · 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 · Hy3 preview 256,000 tokens
- Widest inputsMistral Small 4 and Llama 4 Scout 17B InstructMistral Small 4: Text, Images · Llama 4 Scout 17B Instruct: Text, Images · Hy3 preview: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Small 4 | Llama 4 Scout 17B Instruct | Hy3 preview |
|---|---|---|---|---|
| Price | 50% | 77 | 72 | 76 |
| Inputs & features | 30% | 60 | 50 | 35 |
| Context window | 20% | 36 | 100 | 36 |
| Overall | 100% | 64/100 | 71/100 | 56/100 |
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 | Mistral Small 4Mistral AI | Llama 4 Scout 17B InstructMeta | Hy3 previewTencent |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 129.7 | — |
| ECI rank | — | #126 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 51.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% | — |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.225 | $0.176 |
| Output | $0.60 | $0.69 | $0.586 (best) |
| Cached input | $0.015 | — | — |
| Blended (3:1) | $0.263 (best) | $0.341 | $0.279 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 4 providers | Median of 4 providers |
| Limits | |||
| Context window | 256,000 tokens | 10,000,000 tokens (best) | 256,000 tokens |
| Max output | 256,000 tokens (best) | 16,384 tokens | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeshigh | No | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | mistral-small-2603 | — | hy3-preview |
| API providers | 16 (best) | 4 | 5 |
| Released | Mar 16, 2026 | Apr 5, 2025 | Apr 20, 2026 |
| Knowledge cutoff | Jun 2025 | 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 4$2.70
- Llama 4 Scout 17B Instruct$3.63
- Hy3 preview$2.93
Which should you choose?
Which is better: Mistral Small 4, Llama 4 Scout 17B Instruct or Hy3 preview?
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 71/100 against Mistral Small 4 (64) and Hy3 preview (56). It leads on context window. Mistral Small 4 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, Mistral Small 4, Llama 4 Scout 17B Instruct or Hy3 preview?
Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral API price). Hy3 preview costs $0.176 input / $0.586 output per million tokens (median across 4 API providers; free on Tencent TokenHub); 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 $0.279 for Hy3 preview (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. Mistral Small 4 has not been scored yet, Llama 4 Scout 17B Instruct has an ECI of 129.7 and Hy3 preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 4, Llama 4 Scout 17B Instruct and Hy3 preview 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 256,000 for Hy3 preview. Maximum output per response: Mistral Small 4 up to 256,000, Llama 4 Scout 17B Instruct up to 16,384, Hy3 preview up to 64,000 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 4 accepts text and images; Llama 4 Scout 17B Instruct accepts text and images; Hy3 preview accepts text. Mistral Small 4 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?
Hy3 preview is the newest, released Apr 20, 2026. Mistral Small 4 came out Mar 16, 2026; Llama 4 Scout 17B Instruct came out Apr 5, 2025. Knowledge cutoff: Mistral Small 4 Jun 2025, 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.
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