Llama-3.2-1B vs Llama-3.3-70B-Instruct vs Ministral 8B Instruct
Too close to call on our weighted score (Llama-3.3-70B-Instruct 45, Ministral 8B Instruct 42, Llama-3.2-1B 39). The right pick depends on what you value most.
MetaLlama-3.2-1B
39/100- ECI102.0
- Price$0.064 / $0.15
- Context131K
- Meta
Llama-3.3-70B-Instruct
45/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Mistral AIMinistral 8B Instruct
42/100- ECI—
- Price$0.15 / $0.15
- Context131K
Too close to call
It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 45/100, Ministral 8B Instruct 42/100, Llama-3.2-1B 39/100), so choose by what matters most for your work: Llama-3.3-70B-Instruct for raw capability and Llama-3.2-1B 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.
- CapabilityLlama-3.3-70B-InstructShared benchmarks: Llama-3.3-70B-Instruct 47.4% · 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 · Llama-3.3-70B-Instruct $0.624 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 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsSame inputsLlama-3.2-1B: Text · Llama-3.3-70B-Instruct: Text · 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 | Llama-3.3-70B-Instruct | Ministral 8B Instruct |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 24 | 47 | 27 |
| Price | 25% | 100 | 60 | 89 |
| Inputs & features | 15% | 0 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 39/100 | 45/100 | 42/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.2-1BMeta | Llama-3.3-70B-InstructMeta | Ministral 8B InstructMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 102.0 | 127.3 (best) | — |
| ECI rank | #147 of 148 | #133 of 148 (best) | — |
| GPQA DiamondGraduate-level science questions | 23.9% | 47.4% (best) | 27.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 0.6% | 5.1% (best) | — |
| Price per million tokens | |||
| Input | $0.064 (best) | $0.59 | $0.15 |
| Output | $0.15 | $0.724 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.085 (best) | $0.624 | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 21 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens (best) | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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 | No | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | OpenMistral Research License |
| API model ID | — | llama-3.3-70b-instruct | — |
| API providers | 2 | 24 (best) | 1 |
| Released | Sep 25, 2024 | Dec 6, 2024 | Oct 16, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 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-3.2-1B$0.936
- Llama-3.3-70B-Instruct$7.35
- Ministral 8B Instruct$1.80
Which should you choose?
Which is better: Llama-3.2-1B, Llama-3.3-70B-Instruct or Ministral 8B Instruct?
It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 45/100, Ministral 8B Instruct 42/100, Llama-3.2-1B 39/100), so choose by what matters most for your work: Llama-3.3-70B-Instruct for raw capability and Llama-3.2-1B 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, Llama-3.3-70B-Instruct 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); 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 $0.15 for Ministral 8B Instruct (1.8× as much) and $0.624 for Llama-3.3-70B-Instruct (7.3× 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): Llama-3.3-70B-Instruct 47.4%, Ministral 8B Instruct 27.2% and Llama-3.2-1B 23.9%. On individual benchmarks: GPQA Diamond — Llama-3.3-70B-Instruct 47.4%, 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, Llama-3.3-70B-Instruct and Ministral 8B Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.3-70B-Instruct 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 Llama-3.3-70B-Instruct. Maximum output per response: Llama-3.2-1B up to 8,192, Llama-3.3-70B-Instruct up to 4,096, Ministral 8B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-1B accepts text; Llama-3.3-70B-Instruct accepts text; Ministral 8B Instruct accepts text. They handle the same number of input types.
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?
Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. 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, Llama-3.3-70B-Instruct Dec 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 Oct 4, 2026.
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