Mistral Small 3.2 vs GPT OSS 120B vs Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite comes out ahead, 71 to 61 and 60 on our weighted score, though Mistral Small 3.2 is 14% cheaper per token.
Mistral AIMistral Small 3.2
60/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
OpenAIGPT OSS 120B
61/100- ECI140.0
- Price$0.15 / $0.60
- Context131K
- Our pick
GoogleGemini 2.5 Flash-Lite
71/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT OSS 120B (61) and Mistral Small 3.2 (60). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. GPT OSS 120B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT OSS 120BCapabilities Index (ECI): GPT OSS 120B 140.0 · Gemini 2.5 Flash-Lite 133.9 · Mistral Small 3.2 131.7
- Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · Gemini 2.5 Flash-Lite $0.175 · GPT OSS 120B $0.263 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · GPT OSS 120B 131,072 · Mistral Small 3.2 128,000 tokens
- Widest inputsGemini 2.5 Flash-LiteMistral Small 3.2: Text, Images · GPT OSS 120B: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video
- Self-hostingMistral Small 3.2 and GPT OSS 120BPublishes downloadable weights
| Measure | Weight | Mistral Small 3.2 | GPT OSS 120B | Gemini 2.5 Flash-Lite |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 55 | 65 | 58 |
| Price | 25% | 89 | 77 | 86 |
| Inputs & features | 15% | 50 | 45 | 100 |
| Context window | 10% | 24 | 24 | 61 |
| Overall | 100% | 60/100 | 61/100 | 71/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Small 3.2Mistral AI | GPT OSS 120BOpenAI | Gemini 2.5 Flash-LiteGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 131.7 | 140.0 (best) | 133.9 |
| ECI rank | #123 of 148 | #99 of 148 (best) | #118 of 148 |
| GPQA DiamondGraduate-level science questions | 49.1% | 75.8% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 30.3% | 88.9% (best) | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.15 | $0.10 (best) |
| Output | $0.30 (best) | $0.60 | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.15 (best) | $0.263 | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 36 providers | Official Google API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 1,048,576 tokens (best) |
| Max output | 16,384 tokens | 32,768 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | mistral-small-2506 | — | gemini-2.5-flash-lite |
| API providers | 6 | 39 (best) | 20 |
| Released | Jun 20, 2025 | Aug 5, 2025 | Jun 17, 2025 |
| Knowledge cutoff | Mar 2025 | — | 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.
- Mistral Small 3.2$1.60
- GPT OSS 120B$2.70
- Gemini 2.5 Flash-Lite$1.80
Which should you choose?
Which is better: Mistral Small 3.2, GPT OSS 120B or Gemini 2.5 Flash-Lite?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT OSS 120B (61) and Mistral Small 3.2 (60). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. GPT OSS 120B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Small 3.2, GPT OSS 120B or Gemini 2.5 Flash-Lite?
Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Gemini 2.5 Flash-Lite costs $0.10 input / $0.40 output per million tokens (official Google API price); GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 36 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.175 for Gemini 2.5 Flash-Lite (1.2× as much) and $0.263 for GPT OSS 120B (1.8× as much).
Which scores higher on benchmarks?
GPT OSS 120B scores higher on the Capabilities Index (ECI): GPT OSS 120B 140.0 (#99 of 148), Gemini 2.5 Flash-Lite 133.9 (#118 of 148) and Mistral Small 3.2 131.7 (#123 of 148). The confidence ranges of the top two overlap (135.3–142.3 vs 129.8–136.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 3.2, GPT OSS 120B and Gemini 2.5 Flash-Lite yet, so there is no like-for-like coding score. On overall capability, GPT OSS 120B leads, which tends to carry over to coding, but test on your own codebase. 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 131,072 for GPT OSS 120B and 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, GPT OSS 120B up to 32,768, Gemini 2.5 Flash-Lite up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 3.2 accepts text and images; GPT OSS 120B accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Mistral Small 3.2 and GPT OSS 120B publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
GPT OSS 120B is the newest, released Aug 5, 2025. Mistral Small 3.2 came out Jun 20, 2025; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, 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 Oct 4, 2026.
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