Gemini 2.5 Flash-Lite vs Mistral Small 3.2 vs Qwen3.5 9B
Too close to call on our weighted score (Qwen3.5 9B 72, Gemini 2.5 Flash-Lite 71, Mistral Small 3.2 60). The right pick depends on what you value most.
GoogleGemini 2.5 Flash-Lite
71/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
Mistral AIMistral Small 3.2
60/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
Alibaba (Qwen)Qwen3.5 9B
72/100- ECI139.5
- Price$0.10 / $0.15
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3.5 9B 72/100, Gemini 2.5 Flash-Lite 71/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and Gemini 2.5 Flash-Lite for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · Gemini 2.5 Flash-Lite 133.9 · Mistral Small 3.2 131.7
- Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · Mistral Small 3.2 $0.15 · Gemini 2.5 Flash-Lite $0.175 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen3.5 9B 262,144 · Mistral Small 3.2 128,000 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Mistral Small 3.2: Text, Images · Qwen3.5 9B: Text, Images, Video
- Self-hostingMistral Small 3.2 and Qwen3.5 9BPublishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | Mistral Small 3.2 | Qwen3.5 9B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 58 | 55 | 65 |
| Price | 25% | 86 | 89 | 95 |
| Inputs & features | 15% | 100 | 50 | 80 |
| Context window | 10% | 61 | 24 | 37 |
| Overall | 100% | 71/100 | 60/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 Flash-LiteGoogle | Mistral Small 3.2Mistral AI | Qwen3.5 9BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 133.9 | 131.7 | 139.5 (best) |
| ECI rank | #118 of 148 | #123 of 148 | #101 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 49.1% | 79.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 30.3% | 61.7% (best) |
| Price per million tokens | |||
| Input | $0.10 | $0.10 | $0.10 |
| Output | $0.40 | $0.30 | $0.15 (best) |
| Cached input | $0.01 | — | — |
| Blended (3:1) | $0.175 | $0.15 | $0.113 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official Mistral API | Median of 14 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 128,000 tokens | 262,144 tokens |
| Max output | 65,536 tokens (best) | 16,384 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gemini-2.5-flash-lite | mistral-small-2506 | — |
| API providers | 20 (best) | 6 | 15 |
| Released | Jun 17, 2025 | Jun 20, 2025 | Feb 23, 2026 |
| Knowledge cutoff | Jan 2025 | Mar 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 Small 3.2$1.60
- Qwen3.5 9B$1.30
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, Mistral Small 3.2 or Qwen3.5 9B?
It is close. Our weighted score puts them within a point (Qwen3.5 9B 72/100, Gemini 2.5 Flash-Lite 71/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and Gemini 2.5 Flash-Lite for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 2.5 Flash-Lite, Mistral Small 3.2 or Qwen3.5 9B?
Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). Mistral Small 3.2 costs $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). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.15 for Mistral Small 3.2 (1.3× as much) and $0.175 for Gemini 2.5 Flash-Lite (1.6× as much).
Which scores higher on benchmarks?
Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148), Gemini 2.5 Flash-Lite 133.9 (#118 of 148) and Mistral Small 3.2 131.7 (#123 of 148). Their confidence ranges do not overlap (136.5–141.3 vs 129.8–136.3), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, Mistral Small 3.2 and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B 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 262,144 for Qwen3.5 9B and 128,000 for Mistral Small 3.2. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, Mistral Small 3.2 up to 16,384, Qwen3.5 9B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Mistral Small 3.2 accepts text and images; Qwen3.5 9B accepts text, images and video. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Mistral Small 3.2 and Qwen3.5 9B publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Qwen3.5 9B is the newest, released Feb 23, 2026. Mistral Small 3.2 came out Jun 20, 2025; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, Mistral Small 3.2 Mar 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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