Pixtral 12B vs Llama 3.1 Nemotron Ultra 253B vs Llama-3.2-3B
Too close to call on our weighted score (Llama 3.1 Nemotron Ultra 253B 65, Pixtral 12B 64, Llama-3.2-3B 49). The right pick depends on what you value most.
Mistral AIPixtral 12B
64/100- ECI—
- Price$0.15 / $0.15
- Context128K
NVIDIALlama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Too close to call
It is close. Our weighted score puts them within 1 points (Llama 3.1 Nemotron Ultra 253B 65/100, Pixtral 12B 64/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price and Llama-3.2-3B for long inputs. 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 priceLlama 3.1 Nemotron Ultra 253BLlama 3.1 Nemotron Ultra 253B Free · Pixtral 12B $0.15 · Llama-3.2-3B $0.159 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-3BLlama-3.2-3B 131,072 · Pixtral 12B 128,000 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsPixtral 12BPixtral 12B: Text, Images · Llama 3.1 Nemotron Ultra 253B: Text · Llama-3.2-3B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Pixtral 12B | Llama 3.1 Nemotron Ultra 253B | Llama-3.2-3B |
|---|---|---|---|---|
| Price | 50% | 89 | 100 | 88 |
| Inputs & features | 30% | 50 | 35 | 0 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 64/100 | 65/100 | 49/100 |
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 | Pixtral 12BMistral AI | Llama 3.1 Nemotron Ultra 253BNVIDIA | Llama-3.2-3BMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.15 | Free (best) | $0.10 |
| Output | $0.15 | Free (best) | $0.335 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 | Free (best) | $0.159 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Nvidia API | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 131,072 tokens (best) |
| Max output | 128,000 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | OpenLlama 3.2 Community License |
| API model ID | pixtral-12b | nvidia/llama-3.1-nemotron-ultra-253b-v1 | — |
| API providers | 4 (best) | 1 | 3 |
| Released | Sep 1, 2024 | Apr 7, 2025 | Sep 25, 2024 |
| Knowledge cutoff | Sep 2024 | — | 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.
- Pixtral 12B$1.80
- Llama 3.1 Nemotron Ultra 253BFree
- Llama-3.2-3B$1.67
Which should you choose?
Which is better: Pixtral 12B, Llama 3.1 Nemotron Ultra 253B or Llama-3.2-3B?
It is close. Our weighted score puts them within 1 points (Llama 3.1 Nemotron Ultra 253B 65/100, Pixtral 12B 64/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price and Llama-3.2-3B for long inputs. 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, Pixtral 12B, Llama 3.1 Nemotron Ultra 253B or Llama-3.2-3B?
Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). Pixtral 12B costs $0.15 input / $0.15 output per million tokens (official Mistral API price); Llama-3.2-3B costs $0.10 input / $0.335 output per million tokens (median across 3 API providers). Llama 3.1 Nemotron Ultra 253B is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Pixtral 12B has not been scored yet, Llama 3.1 Nemotron Ultra 253B has not been scored yet and Llama-3.2-3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Pixtral 12B, Llama 3.1 Nemotron Ultra 253B and Llama-3.2-3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-3B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-3B has the largest context window at 131,072 tokens, against 128,000 for Pixtral 12B and 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: Pixtral 12B up to 128,000, Llama 3.1 Nemotron Ultra 253B up to 8,192, Llama-3.2-3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Pixtral 12B accepts text and images; Llama 3.1 Nemotron Ultra 253B accepts text; Llama-3.2-3B accepts text. Pixtral 12B 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?
Llama 3.1 Nemotron Ultra 253B is the newest, released Apr 7, 2025. Llama-3.2-3B came out Sep 25, 2024; Pixtral 12B came out Sep 1, 2024. Knowledge cutoff: Pixtral 12B Sep 2024, Llama-3.2-3B 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.
