Voxtral Small 24B 2507 vs Qwen3-Next 80B-A3B Instruct vs Qwen Flash
Qwen Flash comes out ahead, 68 to 55 and 39 on our weighted score, and it is the cheaper option too.
Mistral AI
Voxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
- Our pick
Alibaba (Qwen)
Qwen Flash
68/100- ECI—
- Price$0.05 / $0.40
- Context1M
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 68/100 against Voxtral Small 24B 2507 (55) and Qwen3-Next 80B-A3B Instruct (39). It leads on price and context window. 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 priceQwen FlashQwen Flash $0.138 · Voxtral Small 24B 2507 $0.15 · Qwen3-Next 80B-A3B Instruct $0.875 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · Qwen3-Next 80B-A3B Instruct 131,072 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507Voxtral Small 24B 2507: Text, Audio · Qwen3-Next 80B-A3B Instruct: Text · Qwen Flash: Text
- Self-hostingVoxtral Small 24B 2507 and Qwen3-Next 80B-A3B InstructPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Voxtral Small 24B 2507 | Qwen3-Next 80B-A3B Instruct | Qwen Flash |
|---|---|---|---|---|
| Price | 50% | 89 | 53 | 91 |
| Inputs & features | 30% | 35 | 25 | 35 |
| Context window | 20% | 0 | 24 | 60 |
| Overall | 100% | 55/100 | 39/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | $0.50 | $0.05 (best) |
| Output | $0.30 (best) | $2.00 | $0.40 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 | $0.875 | $0.138 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 32,768 tokens | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 32,768 tokens | 32,768 tokens |
| 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Proprietary |
| API model ID | voxtral-small-latest | qwen3-next-80b-a3b-instruct | qwen-flash |
| API providers | 7 | 13 (best) | 6 |
| Released | Jul 15, 2025 | Sep 2025 | Jul 28, 2025 |
| Knowledge cutoff | — | Apr 2025 | 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
Qwen3-Next 80B-A3B Instruct$9.00
Qwen Flash$1.30
Which should you choose?
Which is better: Voxtral Small 24B 2507, Qwen3-Next 80B-A3B Instruct or Qwen Flash?
Qwen Flash is the better all-round choice, scoring 68/100 against Voxtral Small 24B 2507 (55) and Qwen3-Next 80B-A3B Instruct (39). It leads on price and context window. 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, Qwen3-Next 80B-A3B Instruct or Qwen Flash?
Qwen Flash is cheaper at $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); Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for Qwen Flash versus $0.15 for Voxtral Small 24B 2507 (1.1× as much) and $0.875 for Qwen3-Next 80B-A3B Instruct (6.4× as much).
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, Qwen3-Next 80B-A3B Instruct 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, Qwen3-Next 80B-A3B Instruct 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 131,072 for Qwen3-Next 80B-A3B Instruct and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Voxtral Small 24B 2507 up to 32,768, Qwen3-Next 80B-A3B Instruct up to 32,768, Qwen Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Voxtral Small 24B 2507 accepts text and audio; Qwen3-Next 80B-A3B Instruct 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 Qwen3-Next 80B-A3B Instruct publishes its weights (Apache 2.0) and can be self-hosted; Qwen Flash is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. Qwen Flash came out Jul 28, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, 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.