Gemini 2.5 Flash-Lite vs Mistral Nemotron vs Voxtral Small 24B 2507
Gemini 2.5 Flash-Lite comes out ahead, 84 to 27 and 25 on our weighted score.
- Our pick
GoogleGemini 2.5 Flash-Lite
84/100- ECI—
- Price$0.10 / $0.40
- Context1.05M
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
Mistral AIVoxtral Small 24B 2507
27/100- ECI—
- Price$0.10 / $0.40
- Context33K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 84/100 against Voxtral Small 24B 2507 (27) and Mistral Nemotron (25). It leads on inputs & features and context window. 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 priceGemini 2.5 Flash-Lite and Voxtral Small 24B 2507Gemini 2.5 Flash-Lite $0.175 · Voxtral Small 24B 2507 $0.175 per 1M tokens (3:1 blend) · Mistral Nemotron unpriced
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Mistral Nemotron 128,000 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Mistral Nemotron: Text · Voxtral Small 24B 2507: Text, Audio
- Self-hostingVoxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Gemini 2.5 Flash-Lite | Mistral Nemotron | Voxtral Small 24B 2507 |
|---|---|---|---|---|
| Inputs & features | 60% | 100 | 25 | 45 |
| Context window | 40% | 61 | 24 | 0 |
| Overall | 100% | 84/100 | 25/100 | 27/100 |
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 | Gemini 2.5 Flash-LiteGoogle | Mistral NemotronNVIDIA | Voxtral Small 24B 2507Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | — | $0.10 |
| Output | $0.40 | — | $0.40 |
| Cached input | $0.01 | — | — |
| Blended (3:1) | $0.175 | — | $0.175 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Google API | — | Official Mistral API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 128,000 tokens | 32,768 tokens |
| Max output | 65,536 tokens (best) | 8,192 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | Yes |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenApache 2.0 |
| API model ID | gemini-2.5-flash-lite | — | voxtral-small-latest |
| API providers | 24 (best) | — | 10 |
| Released | Jun 17, 2025 | Jun 11, 2025 | Jul 15, 2025 |
| Knowledge cutoff | Jan 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.5 Flash-Lite$1.80
- Mistral Nemotron—
- Voxtral Small 24B 2507$1.80
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, Mistral Nemotron or Voxtral Small 24B 2507?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 84/100 against Voxtral Small 24B 2507 (27) and Mistral Nemotron (25). It leads on inputs & features and context window. 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, Gemini 2.5 Flash-Lite, Mistral Nemotron or Voxtral Small 24B 2507?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). Voxtral Small 24B 2507 costs $0.10 input / $0.40 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.175 for Voxtral Small 24B 2507 (1× as much). Mistral Nemotron has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash-Lite has not been scored yet, Mistral Nemotron has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, Mistral Nemotron and Voxtral Small 24B 2507 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?
Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 128,000 for Mistral Nemotron and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, Mistral Nemotron up to 8,192, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Mistral Nemotron accepts text; Voxtral Small 24B 2507 accepts text and audio. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; Gemini 2.5 Flash-Lite and Mistral Nemotron is proprietary.
Which is newer?
Voxtral Small 24B 2507 is the newest, released Jul 15, 2025. Gemini 2.5 Flash-Lite came out Jun 17, 2025; Mistral Nemotron came out Jun 11, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 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 Nov 2, 2026.
