Model comparison
Gemini 2.5 Flash-Lite vs MiniMax-M3
MiniMax-M3 is the stronger model overall, scoring 43.8 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 3.0× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 1 category and MiniMax-M3 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where MiniMax-M3 leads 58.4 to 32.5.
- The biggest single-benchmark swing is DTBench: 62.8% for Gemini 2.5 Flash-Lite and 78.9% for MiniMax-M3.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M3.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.
- MiniMax-M3 has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | MiniMax-M3 | |
|---|---|---|
| Provider | MiniMax | |
| Noometry Index | 37.0 | 43.8 |
| Released | 2025-06-17 | 2026-06-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 66K | 512K |
| Input $ / M tokens | $0.10 | $0.30 |
| Output $ / M tokens | $0.40 | $1.20 |
| Results tracked | 33 | 41 |
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Category by category
Coding MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 38.5 (#173), MiniMax-M3: 41.8 (#118)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Coding | 1373 | 1469 |
| ALE-Bench | 325.9 | 640.02 |
| FrontierCode | — | 14.7% |
| LMArena WebDev | — | 1482 |
| SciCode | — | 47.1% |
| WeirdML | 35.2% | — |
Agentic & Tool Use Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 28.0 (#96), MiniMax-M3: 22.6 (#130)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| APEX-Agents | — | 37.7% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| OSWorld 2.0 | — | 4.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 2,158 |
Reasoning MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 22.2 (#205), MiniMax-M3: 30.1 (#87)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1447 |
| DTBench | 62.8% | 78.9% |
| LMCA | 18.1% | 33.7% |
| Epoch Capabilities Index | 133.94 | 146.95 |
| SimpleBench | — | 45.8% |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 65.1% |
| CritPt | — | 3.7% |
| Chess Puzzles | — | 14% |
| Mystery Game Puzzles | — | 8% |
| Surface Evolver Bench | — | 55% |
| ForecastBench | — | 61.4 |
Math MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 38.0 (#144), MiniMax-M3: 40.0 (#95)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Math | 1373 | 1429 |
| OTIS Mock AIME 2024-2025 | — | 71.1% |
| ProofBench | — | 18% |
| Omni-MATH | 48% | — |
Knowledge MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 32.5 (#210), MiniMax-M3: 58.4 (#35)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Expert | 1373 | 1461 |
| GPQA Diamond | — | 90.9% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 29.1 (#114), MiniMax-M3: 40.2 (#51)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Vision | 1198 | 1253 |
| VPCT | 30% | — |
| LMArena Document | — | 1435 |
Multilingual MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 49.3 (#134), MiniMax-M3: 53.0 (#75)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Non-English | 1369 | 1420 |
| LMArena Chinese | 1404 | 1463 |
| LMArena French | 1388 | 1447 |
| LMArena German | 1389 | 1426 |
| LMArena Japanese | 1359 | 1381 |
| LMArena Korean | 1360 | 1372 |
| LMArena Russian | 1373 | 1428 |
| LMArena Spanish | 1396 | 1432 |
Instruction Following MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 70.0 (#168), MiniMax-M3: 75.5 (#62)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Instruction Following | 1367 | 1433 |
| IFEval | 81% | — |
Long Context MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 33.3 (#262), MiniMax-M3: 44.2 (#72)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Longer Query | 1373 | 1445 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference MiniMax-M3 leads
Gemini 2.5 Flash-Lite: 56.8 (#135), MiniMax-M3: 62.1 (#83)
| Benchmark | Gemini 2.5 Flash-Lite | MiniMax-M3 |
|---|---|---|
| LMArena Text | 1379 | 1433 |
| LMArena Creative Writing | 1367 | 1404 |
| LMArena Multi-Turn | 1366 | 1442 |
| WildBench | 81.8% | — |
| EQ-Bench 4 | — | 1150 |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than MiniMax-M3?
MiniMax-M3 is the stronger model overall, scoring 43.8 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 3.0× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or MiniMax-M3?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; MiniMax-M3 lists at $0.30 and $1.20.
Is Gemini 2.5 Flash-Lite or MiniMax-M3 better for coding?
MiniMax-M3 scores higher on coding benchmarks: 41.8 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 1M.
How many benchmarks do Gemini 2.5 Flash-Lite and MiniMax-M3 share?
22 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and MiniMax-M3 has 41.