Gemma 3n E2B IT vs Mistral Small 3.2 24B vs o3-deep-research
o3-deep-research comes out ahead, 49 to 44 and 21 on our weighted score, though Mistral Small 3.2 24B is 104× cheaper per token.
GoogleGemma 3n E2B IT
21/100- ECI—
- Price—
- Context33K
Mistral AIMistral Small 3.2 24B
44/100- ECI—
- Price$0.10 / $0.305
- Context256K
- Our pick
OpenAIo3-deep-research
49/100- ECI—
- Price$9.00 / $36.00
- Context200K
o3-deep-research is our pick
o3-deep-research is the better all-round choice, scoring 49/100 against Mistral Small 3.2 24B (44) and Gemma 3n E2B IT (21). It leads on inputs & features. Mistral Small 3.2 24B wins on 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 priceMistral Small 3.2 24BMistral Small 3.2 24B $0.151 · o3-deep-research $15.75 per 1M tokens (3:1 blend) · Gemma 3n E2B IT unpriced
- Longest contextMistral Small 3.2 24BMistral Small 3.2 24B 256,000 · o3-deep-research 200,000 · Gemma 3n E2B IT 32,768 tokens
- Widest inputsGemma 3n E2B ITGemma 3n E2B IT: Text, Images, Audio · Mistral Small 3.2 24B: Text, Images · o3-deep-research: Text, Images
- Self-hostingGemma 3n E2B IT and Mistral Small 3.2 24BPublishes downloadable weights (Gemma Terms of Use)
| Measure | Weight | Gemma 3n E2B IT | Mistral Small 3.2 24B | o3-deep-research |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 50 | 60 |
| Context window | 40% | 0 | 36 | 32 |
| Overall | 100% | 21/100 | 44/100 | 49/100 |
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 Small 3.2 24BMistral AI | o3-deep-researchOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.10 (best) | $9.00 |
| Output | — | $0.305 (best) | $36.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.151 (best) | $15.75 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 8 providers | Median of 1 providers |
| Limits | |||
| Context window | 32,768 tokens | 256,000 tokens (best) | 200,000 tokens |
| Max output | 32,768 tokens | 16,384 tokens | 100,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenGemma Terms of Use | Open | Proprietary |
| API model ID | — | — | — |
| API providers | — | 8 (best) | 1 |
| Released | Jun 26, 2025 | Jun 20, 2025 | Jun 26, 2025 |
| Knowledge cutoff | Jun 2024 | Oct 31, 2023 | May 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 Small 3.2 24B$1.61
- o3-deep-research$162.00
Which should you choose?
Which is better: Gemma 3n E2B IT, Mistral Small 3.2 24B or o3-deep-research?
o3-deep-research is the better all-round choice, scoring 49/100 against Mistral Small 3.2 24B (44) and Gemma 3n E2B IT (21). It leads on inputs & features. Mistral Small 3.2 24B wins on 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, Gemma 3n E2B IT, Mistral Small 3.2 24B or o3-deep-research?
Mistral Small 3.2 24B is cheaper at $0.10 input / $0.305 output per million tokens (median across 8 API providers). o3-deep-research costs $9.00 input / $36.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.151 per million tokens for Mistral Small 3.2 24B versus $15.75 for o3-deep-research (104× as much). Gemma 3n E2B IT has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 3n E2B IT has not been scored yet, Mistral Small 3.2 24B has not been scored yet and o3-deep-research has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3n E2B IT, Mistral Small 3.2 24B and o3-deep-research 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 Small 3.2 24B has the largest context window at 256,000 tokens, against 200,000 for o3-deep-research and 32,768 for Gemma 3n E2B IT. Maximum output per response: Gemma 3n E2B IT up to 32,768, Mistral Small 3.2 24B up to 16,384, o3-deep-research up to 100,000 tokens.
Which can read images, PDFs, audio or video?
Gemma 3n E2B IT accepts text, images and audio; Mistral Small 3.2 24B accepts text and images; o3-deep-research accepts text and images. Gemma 3n E2B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3n E2B IT and Mistral Small 3.2 24B publishes its weights (Gemma Terms of Use) and can be self-hosted; o3-deep-research is proprietary.
Which is newer?
Gemma 3n E2B IT is the newest, released Jun 26, 2025. o3-deep-research came out Jun 26, 2025; Mistral Small 3.2 24B came out Jun 20, 2025. Knowledge cutoff: Gemma 3n E2B IT Jun 2024, Mistral Small 3.2 24B Oct 31, 2023, o3-deep-research May 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.
