Gemini 2.5 Flash-Lite vs Qwen3 Coder Next vs Mistral Small 3.2
Gemini 2.5 Flash-Lite comes out ahead, 85 to 64 and 51 on our weighted score, though Mistral Small 3.2 is 14% cheaper per token.
- Our pick
GoogleGemini 2.5 Flash-Lite
85/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
Alibaba (Qwen)Qwen3 Coder Next
51/100- ECI—
- Price$0.20 / $1.20
- Context262K
Mistral AIMistral Small 3.2
64/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Mistral Small 3.2 (64) and Qwen3 Coder Next (51). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. 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 3.2Mistral Small 3.2 $0.15 · Gemini 2.5 Flash-Lite $0.175 · Qwen3 Coder Next $0.45 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen3 Coder Next 262,144 · Mistral Small 3.2 128,000 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Qwen3 Coder Next: Text · Mistral Small 3.2: Text, Images
- Self-hostingQwen3 Coder Next and Mistral Small 3.2Publishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | Qwen3 Coder Next | Mistral Small 3.2 |
|---|---|---|---|---|
| Price | 50% | 86 | 66 | 89 |
| Inputs & features | 30% | 100 | 35 | 50 |
| Context window | 20% | 61 | 37 | 24 |
| Overall | 100% | 85/100 | 51/100 | 64/100 |
Left out because at least one model lacks the data: capability. 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 | Qwen3 Coder NextAlibaba (Qwen) | Mistral Small 3.2Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 133.9 (best) | — | 131.7 |
| ECI rank | #118 of 148 (best) | — | #123 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 49.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 30.3% |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.20 | $0.10 (best) |
| Output | $0.40 | $1.20 | $0.30 (best) |
| Cached input | $0.01 | — | — |
| Blended (3:1) | $0.175 | $0.45 | $0.15 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Median of 11 providers | Official Mistral API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 128,000 tokens |
| Max output | 65,536 tokens (best) | 65,536 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gemini-2.5-flash-lite | — | mistral-small-2506 |
| API providers | 20 (best) | 11 | 6 |
| Released | Jun 17, 2025 | Feb 3, 2026 | Jun 20, 2025 |
| Knowledge cutoff | Jan 2025 | Sep 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
- Qwen3 Coder Next$4.40
- Mistral Small 3.2$1.60
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, Qwen3 Coder Next or Mistral Small 3.2?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Mistral Small 3.2 (64) and Qwen3 Coder Next (51). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. 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, Qwen3 Coder Next or Mistral Small 3.2?
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); Qwen3 Coder Next costs $0.20 input / $1.20 output per million tokens (median across 11 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 $0.45 for Qwen3 Coder Next (3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash-Lite has an ECI of 133.9, Qwen3 Coder Next has not been scored yet and Mistral Small 3.2 has an ECI of 131.7.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, Qwen3 Coder Next and Mistral Small 3.2 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 262,144 for Qwen3 Coder Next and 128,000 for Mistral Small 3.2. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, Qwen3 Coder Next up to 65,536, Mistral Small 3.2 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Qwen3 Coder Next accepts text; Mistral Small 3.2 accepts text and images. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Qwen3 Coder Next and Mistral Small 3.2 publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Qwen3 Coder Next is the newest, released Feb 3, 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, Qwen3 Coder Next Sep 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.
