Llama-3.2-1B vs Mistral Small 3.1 24B vs Ministral 8B Instruct
Mistral Small 3.1 24B comes out ahead, 54 to 42 and 39 on our weighted score, though Llama-3.2-1B is 3.3× cheaper per token.
MetaLlama-3.2-1B
39/100- ECI102.0
- Price$0.064 / $0.15
- Context131K
- Our pick
Mistral AIMistral Small 3.1 24B
54/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
- Mistral AI
Ministral 8B Instruct
42/100- ECI—
- Price$0.15 / $0.15
- Context131K
Mistral Small 3.1 24B is our pick
Mistral Small 3.1 24B is the better all-round choice, scoring 54/100 against Ministral 8B Instruct (42) and Llama-3.2-1B (39). It leads on capability and inputs & features. Llama-3.2-1B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
- CapabilityMistral Small 3.1 24BShared benchmarks: Mistral Small 3.1 24B 47.5% · Ministral 8B Instruct 27.2% · Llama-3.2-1B 23.9%
- Lowest priceLlama-3.2-1BLlama-3.2-1B $0.085 · Ministral 8B Instruct $0.15 · Mistral Small 3.1 24B $0.281 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-1B and Ministral 8B InstructLlama-3.2-1B 131,072 · Ministral 8B Instruct 131,072 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24BLlama-3.2-1B: Text · Mistral Small 3.1 24B: Text, Images · Ministral 8B Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-1B | Mistral Small 3.1 24B | Ministral 8B Instruct |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 24 | 47 | 27 |
| Price | 25% | 100 | 76 | 89 |
| Inputs & features | 15% | 0 | 60 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 39/100 | 54/100 | 42/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.2-1BMeta | Mistral Small 3.1 24BMistral AI | Ministral 8B InstructMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 102.0 | 127.5 (best) | — |
| ECI rank | #147 of 148 | #132 of 148 (best) | — |
| GPQA DiamondGraduate-level science questions | 23.9% | 47.5% (best) | 27.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 0.6% | 5.8% (best) | — |
| Price per million tokens | |||
| Input | $0.064 (best) | $0.229 | $0.15 |
| Output | $0.15 | $0.436 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.085 (best) | $0.281 | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | OpenMistral Research License |
| API model ID | — | — | — |
| API providers | 2 (best) | 2 (best) | 1 |
| Released | Sep 25, 2024 | Mar 17, 2025 | Oct 16, 2024 |
| Knowledge cutoff | Dec 2023 | 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-3.2-1B$0.936
- Mistral Small 3.1 24B$3.16
- Ministral 8B Instruct$1.80
Which should you choose?
Which is better: Llama-3.2-1B, Mistral Small 3.1 24B or Ministral 8B Instruct?
Mistral Small 3.1 24B is the better all-round choice, scoring 54/100 against Ministral 8B Instruct (42) and Llama-3.2-1B (39). It leads on capability and inputs & features. Llama-3.2-1B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
Which is cheaper, Llama-3.2-1B, Mistral Small 3.1 24B or Ministral 8B Instruct?
Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 API providers). Ministral 8B Instruct costs $0.15 input / $0.15 output per million tokens (median across 1 API provider); Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.085 per million tokens for Llama-3.2-1B versus $0.15 for Ministral 8B Instruct (1.8× as much) and $0.281 for Mistral Small 3.1 24B (3.3× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Mistral Small 3.1 24B 47.5%, Ministral 8B Instruct 27.2% and Llama-3.2-1B 23.9%. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Ministral 8B Instruct 27.2%, Llama-3.2-1B 23.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-1B, Mistral Small 3.1 24B and Ministral 8B Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.1 24B leads, which tends to carry over to coding, but test on your own codebase. Note that Llama-3.2-1B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-1B and Ministral 8B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama-3.2-1B up to 8,192, Mistral Small 3.1 24B up to 16,384, Ministral 8B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-1B accepts text; Mistral Small 3.1 24B accepts text and images; Ministral 8B Instruct accepts text. Mistral Small 3.1 24B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Llama 3.2 Community License and Mistral Research License), so you can self-host them.
Which is newer?
Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Ministral 8B Instruct came out Oct 16, 2024; Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-1B Dec 2023, 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.
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