Gemma 3n E2B IT vs Mistral Nemotron
Mistral Nemotron comes out ahead, 25 to 21 on our weighted score.
GoogleGemma 3n E2B IT
21/100- ECI—
- Price—
- Context33K
- Our pick
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
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Make it a three-way comparison.
Mistral Nemotron is our pick
Mistral Nemotron is the better all-round choice, scoring 25/100 against Gemma 3n E2B IT (21). It leads on context window. Gemma 3n E2B IT wins on inputs & features. 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
- Longest contextMistral NemotronMistral Nemotron 128,000 · Gemma 3n E2B IT 32,768 tokens
- Widest inputsGemma 3n E2B ITGemma 3n E2B IT: Text, Images, Audio · Mistral Nemotron: Text
- Self-hostingGemma 3n E2B ITPublishes downloadable weights (Gemma Terms of Use)
| Measure | Weight | Gemma 3n E2B IT | Mistral Nemotron |
|---|---|---|---|
| Inputs & features | 60% | 35 | 25 |
| Context window | 40% | 0 | 24 |
| Overall | 100% | 21/100 | 25/100 |
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 | Gemma 3n E2B ITGoogle | Mistral NemotronNVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | — | — |
| Output | — | — |
| Cached input | — | — |
| Blended (3:1) | — | — |
| Long-context rate | — | — |
| Price source | — | — |
| Limits | ||
| Context window | 32,768 tokens | 128,000 tokens (best) |
| Max output | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | Yes | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | No | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenGemma Terms of Use | Proprietary |
| API model ID | — | — |
| API providers | — | — |
| Released | Jun 26, 2025 | Jun 11, 2025 |
| Knowledge cutoff | Jun 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemma 3n E2B IT—
- Mistral Nemotron—
Which should you choose?
Which is better: Gemma 3n E2B IT or Mistral Nemotron?
Mistral Nemotron is the better all-round choice, scoring 25/100 against Gemma 3n E2B IT (21). It leads on context window. Gemma 3n E2B IT wins on inputs & features. 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, Gemma 3n E2B IT or Mistral Nemotron?
None of these models has a published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Gemma 3n E2B IT has not been scored yet and Mistral Nemotron has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3n E2B IT and Mistral Nemotron yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Gemma 3n E2B IT does not support tool calling, which most coding agents need.
Which has the bigger context window?
Mistral Nemotron has the largest context window at 128,000 tokens, against 32,768 for Gemma 3n E2B IT. Maximum output per response: Gemma 3n E2B IT up to 32,768, Mistral Nemotron up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemma 3n E2B IT accepts text, images and audio; Mistral Nemotron accepts text. Gemma 3n E2B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3n E2B IT publishes its weights (Gemma Terms of Use) and can be self-hosted; Mistral Nemotron is proprietary.
Which is newer?
Gemma 3n E2B IT is the newest, released Jun 26, 2025. Mistral Nemotron came out Jun 11, 2025. Knowledge cutoff: Gemma 3n E2B IT Jun 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 Nov 2, 2026.
