Model comparison
Gemini 3.5 Flash-Lite vs MiniMax M2.7
Head-to-head evidence from 15 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.5 Flash-Lite unranked (Not scored); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.5 Flash-Lite and MiniMax M2.7 share 15 comparable benchmark results. 2 of 8 categories are comparable. 6 results are unique to Gemini 3.5 Flash-Lite; 20 to MiniMax M2.7.
Updated July 21, 2026- Shared results
- 15
- Gemini 3.5 Flash-Lite only
- 6
- MiniMax M2.7 only
- 20
- Comparable categories
- 2 / 8
Treat this as a split decision. Gemini 3.5 Flash-Lite makes more sense if agentic is the priority or you need the larger 1M context window; MiniMax M2.7 is the better fit if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 4 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemini 3.5 Flash-Lite and MiniMax M2.7 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Gemini 3.5 Flash-Lite is also the more expensive model on tokens at $0.30 input / $2.50 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 2.1x on output cost alone. Gemini 3.5 Flash-Lite is the reasoning model in the pair, while MiniMax M2.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 3.5 Flash-Lite gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Gemini 3.5 Flash-Lite | Δ | MiniMax M2.7 |
|---|---|---|---|
| Agentic | Gemini 3.5 Flash-Lite63.4 | Margin← 6.4 | MiniMax M2.757.0 |
| Coding | Gemini 3.5 Flash-Lite54.2 | Margin← 0.9 | MiniMax M2.753.3 |
| Reasoning | Gemini 3.5 Flash-Lite72.2 | MarginNo overlap | MiniMax M2.7Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 54%B 57%Winner: MiniMax M2.7Δ 3Terminal-Bench 2.0: Gemini 3.5 Flash-Lite scored 54%; MiniMax M2.7 scored 57%. MiniMax M2.7 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 54.2%B 56.2%Winner: MiniMax M2.7Δ 2SWE-bench Pro: Gemini 3.5 Flash-Lite scored 54.2%; MiniMax M2.7 scored 56.2%. MiniMax M2.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.5 Flash-Lite$0.3 input / $2.5 output | MiniMax M2.7$0.3 input / $1.2 output | MiniMax M2.7 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.5 Flash-LiteNot available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.5 Flash-LiteNot available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.5 Flash-Lite1M | MiniMax M2.7200K | Gemini 3.5 Flash-Lite lists the larger context window. |
Benchmark Deep Dive
AgenticGemini 3.5 Flash-Lite wins14 benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 54% | 57% | MiniMax M2.7 leads |
| OSWorld-VerifiedSource | 74% | — | Not comparable |
| GDPval-AASource | 1140 | 1158 | MiniMax M2.7 leads |
| AA Agentic IndexSource | 26.8% | 25.6% | Gemini 3.5 Flash-Lite leads |
| GDPval-AASource | 32.0% | 32.9% | MiniMax M2.7 leads |
| AA BriefcaseSource | 634 | — | Not comparable |
| AA Tau3 BankingSource | 16.5% | — | Not comparable |
| τ²-bench resultsSource | — | 84.8% | Not comparable |
| ToolathlonSource | — | 46.3% | Not comparable |
| MLE-Bench LiteSource | — | 66.6% | Not comparable |
| MM-ClawBenchSource | — | 62.7% | Not comparable |
| Claw-EvalSource | — | 48.7% | Not comparable |
| APEX-Agents-AASource | — | 10.6% | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
CodingGemini 3.5 Flash-Lite wins12 benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 54.0% | — | Not comparable |
| SWE-bench ProSource | 54.2% | 56.2% | MiniMax M2.7 leads |
| AA Coding IndexSource | 49.3% | 52.6% | MiniMax M2.7 leads |
| AA-SciCodeSource | 40.9% | 47.0% | MiniMax M2.7 leads |
| SWE-bench Verified*Source | — | 75.4% | Not comparable |
| SWE-RebenchSource | — | 51.9% | Not comparable |
| SWE MultilingualSource | — | 76.5% | Not comparable |
| Multi-SWE BenchSource | — | 52.7% | Not comparable |
| VIBE-ProSource | — | 55.6% | Not comparable |
| NL2RepoSource | — | 39.8% | Not comparable |
| Vibe Code BenchSource | — | 27.04% | Not comparable |
| React Native EvalsSource | — | 71.4% | Not comparable |
Reasoning3 benchmarks
Knowledge8 benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 36.5% | 38.1% | MiniMax M2.7 leads |
| AA-GPQA DiamondSource | 83.8% | 87.4% | MiniMax M2.7 leads |
| AA-HLESource | 17.5% | 28.1% | MiniMax M2.7 leads |
| AA-Omniscience IndexSource | 6.9% | 0.7% | Gemini 3.5 Flash-Lite leads |
| AA-Omniscience AccuracySource | 30.3% | 26.1% | Gemini 3.5 Flash-Lite leads |
| AA-Omniscience Hallucination RateSource | 33.5% | 34.4% | Gemini 3.5 Flash-Lite leads |
| GPQA-DSource | — | 87.0% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 80.8% | Not comparable |
Math1 benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | — | 80.0% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | MiniMax M2.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.7% | Not comparable |
Frequently Asked Questions (3)
Which is better, Gemini 3.5 Flash-Lite or MiniMax M2.7?
Gemini 3.5 Flash-Lite and MiniMax M2.7 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Gemini 3.5 Flash-Lite or MiniMax M2.7?
Gemini 3.5 Flash-Lite has the edge for coding in this comparison, averaging 54.2 versus 53.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Gemini 3.5 Flash-Lite or MiniMax M2.7?
Gemini 3.5 Flash-Lite has the edge for agentic tasks in this comparison, averaging 63.4 versus 57. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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