Voxtral Small 24B 2507 vs Llama 3.1 Nemotron Ultra 253B vs Qwen Flash
Too close to call on our weighted score (Qwen Flash 68, Llama 3.1 Nemotron Ultra 253B 65, Voxtral Small 24B 2507 55). The right pick depends on what you value most.
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
NVIDIALlama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
Alibaba (Qwen)Qwen Flash
68/100- ECI—
- Price$0.05 / $0.40
- Context1M
Too close to call
It is close. Our weighted score puts them within 3 points (Qwen Flash 68/100, Llama 3.1 Nemotron Ultra 253B 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price and Qwen Flash 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 · Qwen Flash $0.138 · Voxtral Small 24B 2507 $0.15 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · Llama 3.1 Nemotron Ultra 253B 128,000 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507Voxtral Small 24B 2507: Text, Audio · Llama 3.1 Nemotron Ultra 253B: Text · Qwen Flash: Text
- Self-hostingVoxtral Small 24B 2507 and Llama 3.1 Nemotron Ultra 253BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Voxtral Small 24B 2507 | Llama 3.1 Nemotron Ultra 253B | Qwen Flash |
|---|---|---|---|---|
| Price | 50% | 89 | 100 | 91 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 0 | 24 | 60 |
| Overall | 100% | 55/100 | 65/100 | 68/100 |
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 | Voxtral Small 24B 2507Mistral AI | Llama 3.1 Nemotron Ultra 253BNVIDIA | Qwen FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | Free (best) | $0.05 |
| Output | $0.30 | Free (best) | $0.40 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 | Free (best) | $0.138 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Nvidia API | Official Alibaba API |
| Limits | |||
| Context window | 32,768 tokens | 128,000 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens (best) | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Proprietary |
| API model ID | voxtral-small-latest | nvidia/llama-3.1-nemotron-ultra-253b-v1 | qwen-flash |
| API providers | 7 (best) | 1 | 6 |
| Released | Jul 15, 2025 | Apr 7, 2025 | Jul 28, 2025 |
| Knowledge cutoff | — | — | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Voxtral Small 24B 2507$1.60
- Llama 3.1 Nemotron Ultra 253BFree
- Qwen Flash$1.30
Which should you choose?
Which is better: Voxtral Small 24B 2507, Llama 3.1 Nemotron Ultra 253B or Qwen Flash?
It is close. Our weighted score puts them within 3 points (Qwen Flash 68/100, Llama 3.1 Nemotron Ultra 253B 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B on price and Qwen Flash 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, Voxtral Small 24B 2507, Llama 3.1 Nemotron Ultra 253B or Qwen Flash?
Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). Qwen Flash costs $0.05 input / $0.40 output per million tokens (official Alibaba API price); Voxtral Small 24B 2507 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). 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. Voxtral Small 24B 2507 has not been scored yet, Llama 3.1 Nemotron Ultra 253B has not been scored yet and Qwen Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Voxtral Small 24B 2507, Llama 3.1 Nemotron Ultra 253B and Qwen Flash 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?
Qwen Flash has the largest context window at 1,000,000 tokens, against 128,000 for Llama 3.1 Nemotron Ultra 253B and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Voxtral Small 24B 2507 up to 32,768, Llama 3.1 Nemotron Ultra 253B up to 8,192, Qwen Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Voxtral Small 24B 2507 accepts text and audio; Llama 3.1 Nemotron Ultra 253B accepts text; Qwen Flash accepts text. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
Voxtral Small 24B 2507 and Llama 3.1 Nemotron Ultra 253B publishes its weights (Apache 2.0) and can be self-hosted; Qwen Flash is proprietary.
Which is newer?
Qwen Flash is the newest, released Jul 28, 2025. Voxtral Small 24B 2507 came out Jul 15, 2025; Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025. Knowledge cutoff: Qwen Flash Apr 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.
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