Aya Vision 8B vs Llama 3.1 Nemotron Ultra 253B vs Magistral Medium
Too close to call on our weighted score (Llama 3.1 Nemotron Ultra 253B 31, Magistral Medium 31, Aya Vision 8B 15). The right pick depends on what you value most.
CohereAya Vision 8B
15/100- ECI—
- Price—
- Context16K
NVIDIALlama 3.1 Nemotron Ultra 253B
31/100- ECI—
- PriceFree / Free
- Context128K
Mistral AIMagistral Medium
31/100- ECI—
- Price$2.00 / $5.00
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Llama 3.1 Nemotron Ultra 253B 31/100, Magistral Medium 31/100, Aya Vision 8B 15/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price. The score weighs inputs & features 60%, context window 40%. 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 · Magistral Medium $2.75 per 1M tokens (3:1 blend) · Aya Vision 8B unpriced
- Longest contextLlama 3.1 Nemotron Ultra 253B and Magistral MediumLlama 3.1 Nemotron Ultra 253B 128,000 · Magistral Medium 128,000 · Aya Vision 8B 16,000 tokens
- Widest inputsAya Vision 8BAya Vision 8B: Text, Images · Llama 3.1 Nemotron Ultra 253B: Text · Magistral Medium: Text
- Self-hostingAya Vision 8B and Llama 3.1 Nemotron Ultra 253BPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Aya Vision 8B | Llama 3.1 Nemotron Ultra 253B | Magistral Medium |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 35 | 35 |
| Context window | 40% | 0 | 24 | 24 |
| Overall | 100% | 15/100 | 31/100 | 31/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Aya Vision 8BCohere | Llama 3.1 Nemotron Ultra 253BNVIDIA | Magistral MediumMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | Free (best) | $2.00 |
| Output | — | Free (best) | $5.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | Free (best) | $2.75 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Nvidia API | Official Mistral API |
| Limits | |||
| Context window | 16,000 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 4,000 tokens | 8,192 tokens | 16,384 tokens (best) |
| 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 | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenCC-BY-NC-4.0 | Open | Proprietary |
| API model ID | — | nvidia/llama-3.1-nemotron-ultra-253b-v1 | magistral-medium-latest |
| API providers | — | 1 | 4 (best) |
| Released | Mar 4, 2025 | Apr 7, 2025 | Mar 17, 2025 |
| Knowledge cutoff | — | — | Jun 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Aya Vision 8B—
- Llama 3.1 Nemotron Ultra 253BFree
- Magistral Medium$30.00
Which should you choose?
Which is better: Aya Vision 8B, Llama 3.1 Nemotron Ultra 253B or Magistral Medium?
It is close. Our weighted score puts them within a point (Llama 3.1 Nemotron Ultra 253B 31/100, Magistral Medium 31/100, Aya Vision 8B 15/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Aya Vision 8B, Llama 3.1 Nemotron Ultra 253B or Magistral Medium?
Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). Magistral Medium costs $2.00 input / $5.00 output per million tokens (official Mistral API price). Llama 3.1 Nemotron Ultra 253B is listed as free. Aya Vision 8B has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Aya Vision 8B has not been scored yet, Llama 3.1 Nemotron Ultra 253B has not been scored yet and Magistral Medium has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Aya Vision 8B, Llama 3.1 Nemotron Ultra 253B and Magistral Medium yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Vision 8B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama 3.1 Nemotron Ultra 253B and Magistral Medium have the largest context windows (128,000 and 128,000 tokens), against 16,000 for Aya Vision 8B. Maximum output per response: Aya Vision 8B up to 4,000, Llama 3.1 Nemotron Ultra 253B up to 8,192, Magistral Medium up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Aya Vision 8B accepts text and images; Llama 3.1 Nemotron Ultra 253B accepts text; Magistral Medium accepts text. Aya Vision 8B handles the widest range of inputs.
Are any of these open source?
Aya Vision 8B and Llama 3.1 Nemotron Ultra 253B publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Magistral Medium is proprietary.
Which is newer?
Llama 3.1 Nemotron Ultra 253B is the newest, released Apr 7, 2025. Magistral Medium came out Mar 17, 2025; Aya Vision 8B came out Mar 4, 2025. Knowledge cutoff: Magistral Medium Jun 2025.
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.
