Llama-3.2-1B vs Llama-3.3-70B-Instruct vs Mistral Small 3.1 24B
Mistral Small 3.1 24B comes out ahead, 55 to 46 and 36 on our weighted score, though Llama-3.2-1B is 3.3× cheaper per token.
MetaLlama-3.2-1B
36/100- ECI102.0
- Price$0.064 / $0.15
- Context131K
- Meta
Llama-3.3-70B-Instruct
46/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
- Our pick
Mistral AIMistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
Mistral Small 3.1 24B is our pick
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.3-70B-Instruct (46) and Llama-3.2-1B (36). It leads on inputs & features. Llama-3.2-1B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Small 3.1 24BCapabilities Index (ECI): Mistral Small 3.1 24B 127.5 · Llama-3.3-70B-Instruct 127.3 · Llama-3.2-1B 102.0
- Lowest priceLlama-3.2-1BLlama-3.2-1B $0.085 · Mistral Small 3.1 24B $0.281 · Llama-3.3-70B-Instruct $0.624 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-1BLlama-3.2-1B 131,072 · Llama-3.3-70B-Instruct 128,000 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24BLlama-3.2-1B: Text · Llama-3.3-70B-Instruct: Text · 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-3.2-1B | Llama-3.3-70B-Instruct | Mistral Small 3.1 24B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 17 | 49 | 50 |
| Price | 25% | 100 | 60 | 76 |
| Inputs & features | 15% | 0 | 25 | 60 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 36/100 | 46/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.2-1BMeta | Llama-3.3-70B-InstructMeta | Mistral Small 3.1 24BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 102.0 | 127.3 | 127.5 (best) |
| ECI rank | #147 of 148 | #133 of 148 | #132 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 23.9% | 47.4% | 47.5% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 0.6% | 5.1% | 5.8% (best) |
| Price per million tokens | |||
| Input | $0.064 (best) | $0.59 | $0.229 |
| Output | $0.15 (best) | $0.724 | $0.436 |
| Cached input | — | — | — |
| Blended (3:1) | $0.085 (best) | $0.624 | $0.281 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 21 providers | Median of 2 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens | 4,096 tokens | 16,384 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | Open |
| API model ID | — | llama-3.3-70b-instruct | — |
| API providers | 2 | 24 (best) | 2 |
| Released | Sep 25, 2024 | Dec 6, 2024 | Mar 17, 2025 |
| Knowledge cutoff | Dec 2023 | 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
- Llama-3.3-70B-Instruct$7.35
- Mistral Small 3.1 24B$3.16
Which should you choose?
Which is better: Llama-3.2-1B, Llama-3.3-70B-Instruct or Mistral Small 3.1 24B?
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.3-70B-Instruct (46) and Llama-3.2-1B (36). It leads on inputs & features. Llama-3.2-1B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Llama-3.2-1B, Llama-3.3-70B-Instruct or Mistral Small 3.1 24B?
Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 API providers). Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers); Llama-3.3-70B-Instruct costs $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). 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 $0.281 for Mistral Small 3.1 24B (3.3× as much) and $0.624 for Llama-3.3-70B-Instruct (7.3× as much).
Which scores higher on benchmarks?
Mistral Small 3.1 24B scores higher on the Capabilities Index (ECI): Mistral Small 3.1 24B 127.5 (#132 of 148), Llama-3.3-70B-Instruct 127.3 (#133 of 148) and Llama-3.2-1B 102.0 (#147 of 148). The confidence ranges of the top two overlap (122.6–129.4 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Llama-3.3-70B-Instruct 47.4%, Llama-3.2-1B 23.9%; OTIS Mock AIME 2024–2025 — Mistral Small 3.1 24B 5.8%, Llama-3.3-70B-Instruct 5.1%, Llama-3.2-1B 0.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-1B, Llama-3.3-70B-Instruct and Mistral Small 3.1 24B 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 has the largest context window at 131,072 tokens, against 128,000 for Llama-3.3-70B-Instruct and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama-3.2-1B up to 8,192, Llama-3.3-70B-Instruct up to 4,096, Mistral Small 3.1 24B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-1B accepts text; Llama-3.3-70B-Instruct accepts text; Mistral Small 3.1 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 (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Llama-3.3-70B-Instruct came out Dec 6, 2024; Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-1B Dec 2023, Llama-3.3-70B-Instruct 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.
