Llama-3.3-70B-Instruct vs Mistral Small 3.1 24B vs Mistral Small 3.2 24B
Mistral Small 3.2 24B comes out ahead, 65 to 53 and 41 on our weighted score, and it is the cheaper option too.
MetaLlama-3.3-70B-Instruct
41/100- ECI127.3
- Price$0.59 / $0.753
- Context128K
Mistral AIMistral Small 3.1 24B
53/100- ECI127.5
- Price$0.351 / $0.555
- Context128K
- Our pickMistral AI
Mistral Small 3.2 24B
65/100- ECI—
- Price$0.10 / $0.305
- Context256K
Mistral Small 3.2 24B is our pick
Mistral Small 3.2 24B is the better all-round choice, scoring 65/100 against Mistral Small 3.1 24B (53) and Llama-3.3-70B-Instruct (41). It leads on price and 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 3.2 24BMistral Small 3.2 24B $0.151 · Mistral Small 3.1 24B $0.402 · Llama-3.3-70B-Instruct $0.631 per 1M tokens (3:1 blend)
- Longest contextMistral Small 3.2 24BMistral Small 3.2 24B 256,000 · Llama-3.3-70B-Instruct 128,000 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24B and Mistral Small 3.2 24BLlama-3.3-70B-Instruct: Text · Mistral Small 3.1 24B: Text, Images · Mistral Small 3.2 24B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.3-70B-Instruct | Mistral Small 3.1 24B | Mistral Small 3.2 24B |
|---|---|---|---|---|
| Price | 50% | 57 | 66 | 85 |
| Inputs & features | 30% | 25 | 50 | 50 |
| Context window | 20% | 24 | 24 | 36 |
| Overall | 100% | 41/100 | 53/100 | 65/100 |
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-3.3-70B-InstructMeta | Mistral Small 3.1 24BMistral AI | Mistral Small 3.2 24BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.3 | 127.5 (best) | — |
| ECI rank | #146 of 165 | #145 of 165 (best) | — |
| GPQA DiamondGraduate-level science questions | 47.4% | 47.5% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 5.1% | 5.8% (best) | — |
| Price per million tokens | |||
| Input | $0.59 | $0.351 | $0.10 (best) |
| Output | $0.753 | $0.555 | $0.305 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.631 | $0.402 | $0.151 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 37 providers | Median of 9 providers | Median of 8 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 256,000 tokens (best) |
| Max output | 4,096 tokens | 16,384 tokens (best) | 16,384 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | — |
| API providers | 40 (best) | 9 | 8 |
| Released | Dec 6, 2024 | Mar 17, 2025 | Jun 20, 2025 |
| Knowledge cutoff | Dec 2023 | Jun 2024 | Oct 31, 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.3-70B-Instruct$7.41
- Mistral Small 3.1 24B$4.62
- Mistral Small 3.2 24B$1.61
Which should you choose?
Which is better: Llama-3.3-70B-Instruct, Mistral Small 3.1 24B or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is the better all-round choice, scoring 65/100 against Mistral Small 3.1 24B (53) and Llama-3.3-70B-Instruct (41). It leads on price and 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-3.3-70B-Instruct, Mistral Small 3.1 24B or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is cheaper at $0.10 input / $0.305 output per million tokens (median across 8 API providers). Mistral Small 3.1 24B costs $0.351 input / $0.555 output per million tokens (median across 9 API providers); Llama-3.3-70B-Instruct costs $0.59 input / $0.753 output per million tokens (median across 37 API providers). At a typical mix of three input tokens to one output token, that is $0.151 per million tokens for Mistral Small 3.2 24B versus $0.402 for Mistral Small 3.1 24B (2.7× as much) and $0.631 for Llama-3.3-70B-Instruct (4.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.3-70B-Instruct has an ECI of 127.3, Mistral Small 3.1 24B has an ECI of 127.5 and Mistral Small 3.2 24B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.3-70B-Instruct, Mistral Small 3.1 24B and Mistral Small 3.2 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?
Mistral Small 3.2 24B has the largest context window at 256,000 tokens, against 128,000 for Llama-3.3-70B-Instruct and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama-3.3-70B-Instruct up to 4,096, Mistral Small 3.1 24B up to 16,384, Mistral Small 3.2 24B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Llama-3.3-70B-Instruct accepts text; Mistral Small 3.1 24B accepts text and images; Mistral Small 3.2 24B 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?
Mistral Small 3.2 24B is the newest, released Jun 20, 2025. Mistral Small 3.1 24B came out Mar 17, 2025; Llama-3.3-70B-Instruct came out Dec 6, 2024. Knowledge cutoff: Llama-3.3-70B-Instruct Dec 2023, Mistral Small 3.1 24B Jun 2024, Mistral Small 3.2 24B Oct 31, 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 Nov 2, 2026.
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