Mistral Small 3.2 vs DeepSeek V3 0324 vs Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite comes out ahead, 71 to 60 and 54 on our weighted score, though Mistral Small 3.2 is 14% cheaper per token.
Mistral AI
Mistral Small 3.2
60/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
DeepSeek
DeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
- Our pick
Google
Gemini 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 Mistral Small 3.2 (60) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. DeepSeek V3 0324 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V3 0324Capabilities Index (ECI): DeepSeek V3 0324 135.9 · 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 · DeepSeek V3 0324 $0.405 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · DeepSeek V3 0324 163,840 · Mistral Small 3.2 128,000 tokens
- Widest inputsGemini 2.5 Flash-LiteMistral Small 3.2: Text, Images · DeepSeek V3 0324: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video
- Self-hostingMistral Small 3.2 and DeepSeek V3 0324Publishes downloadable weights
| Measure | Weight | Mistral Small 3.2 | DeepSeek V3 0324 | Gemini 2.5 Flash-Lite |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 55 | 60 | 58 |
| Price | 25% | 89 | 68 | 86 |
| Inputs & features | 15% | 50 | 25 | 100 |
| Context window | 10% | 24 | 28 | 61 |
| Overall | 100% | 60/100 | 54/100 | 71/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 131.7 | 135.9 (best) | 133.9 |
| ECI rank | #123 of 148 | #114 of 148 (best) | #118 of 148 |
| GPQA DiamondGraduate-level science questions | 49.1% | 67.6% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 30.3% | 37.8% (best) | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.24 | $0.10 (best) |
| Output | $0.30 (best) | $0.90 | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.15 (best) | $0.405 | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 5 providers | Official Google API |
| Limits | |||
| Context window | 128,000 tokens | 163,840 tokens | 1,048,576 tokens (best) |
| Max output | 16,384 tokens | 163,840 tokens (best) | 65,536 tokens |
| 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | mistral-small-2506 | — | gemini-2.5-flash-lite |
| API providers | 6 | 5 | 20 (best) |
| Released | Jun 20, 2025 | Mar 24, 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
DeepSeek V3 0324$4.20
Gemini 2.5 Flash-Lite$1.80
Which should you choose?
Which is better: Mistral Small 3.2, DeepSeek V3 0324 or Gemini 2.5 Flash-Lite?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against Mistral Small 3.2 (60) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. DeepSeek V3 0324 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Small 3.2, DeepSeek V3 0324 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); DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 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 $0.405 for DeepSeek V3 0324 (2.7× as much).
Which scores higher on benchmarks?
DeepSeek V3 0324 scores higher on the Capabilities Index (ECI): DeepSeek V3 0324 135.9 (#114 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 (132.4–138.0 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, DeepSeek V3 0324 and Gemini 2.5 Flash-Lite yet, so there is no like-for-like coding score. On overall capability, DeepSeek V3 0324 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 163,840 for DeepSeek V3 0324 and 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, DeepSeek V3 0324 up to 163,840, 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; DeepSeek V3 0324 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 DeepSeek V3 0324 publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Mistral Small 3.2 is the newest, released Jun 20, 2025. Gemini 2.5 Flash-Lite came out Jun 17, 2025; DeepSeek V3 0324 came out Mar 24, 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.