Model comparison
Laguna XS.2 vs MiniMax M2.7
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Laguna XS.2 unranked (Not scored); MiniMax M2.7 #40 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Laguna XS.2 and MiniMax M2.7 share 3 comparable benchmark results. 2 of 8 categories are comparable. 2 results are unique to Laguna XS.2; 32 to MiniMax M2.7.
Updated July 27, 2026- Shared results
- 3
- Laguna XS.2 only
- 2
- MiniMax M2.7 only
- 32
- Comparable categories
- 2 / 8
Treat this as a split decision. Laguna XS.2 makes more sense if coding is the priority or you want the cheaper token bill; MiniMax M2.7 is the better fit if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 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
Laguna XS.2 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.
MiniMax M2.7 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna XS.2. That is roughly Infinityx on output cost alone. Laguna XS.2 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. Laguna XS.2 gives you the larger context window at 256K, 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 | Laguna XS.2 | Δ | MiniMax M2.7 |
|---|---|---|---|
| Agentic | Laguna XS.235.7 | Margin→ 21.3 | MiniMax M2.757.0 |
| Coding | Laguna XS.260.8 | Margin← 7.5 | MiniMax M2.753.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 35.7%B 57%Winner: MiniMax M2.7Δ 21.3Terminal-Bench 2.0: Laguna XS.2 scored 35.7%; MiniMax M2.7 scored 57%. MiniMax M2.7 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 46.3%B 56.2%Winner: MiniMax M2.7Δ 9.9SWE-bench Pro: Laguna XS.2 scored 46.3%; 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 | Laguna XS.2 | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Laguna XS.2$0 input / $0 output | MiniMax M2.7$0.3 input / $1.2 output | Laguna XS.2 has the lower combined listed price. |
| Generation speedtokens per second | Laguna XS.2Not available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Laguna XS.2Not available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Laguna XS.2256K | MiniMax M2.7200K | Laguna XS.2 lists the larger context window. |
Benchmark Deep Dive
AgenticMiniMax M2.7 wins11 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 35.7% | 57% | MiniMax M2.7 leads |
| 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 |
| AA Agentic IndexSource | — | 25.6% | Not comparable |
| APEX-Agents-AASource | — | 10.6% | Not comparable |
| GDPval-AASource | — | 32.9% | Not comparable |
| GDPval-AASource | — | 1159 | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
CodingLaguna XS.2 wins13 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 69.9% | — | Not comparable |
| SWE MultilingualSource | 57.7% | 76.5% | MiniMax M2.7 leads |
| SWE-bench ProSource | 46.3% | 56.2% | MiniMax M2.7 leads |
| Terminal-Bench 2.0Source | 35.7% | — | Not comparable |
| SWE-bench Verified*Source | — | 75.4% | Not comparable |
| SWE-RebenchSource | — | 51.9% | 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 |
| AA Coding IndexSource | — | 52.6% | Not comparable |
| AA-SciCodeSource | — | 47.0% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| GPQA-DSource | — | 87.0% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 80.8% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 38.1% | Not comparable |
| AA-GPQA DiamondSource | — | 87.4% | Not comparable |
| AA-HLESource | — | 28.1% | Not comparable |
| AA-Omniscience IndexSource | — | 0.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 26.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 34.4% | Not comparable |
Math1 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | — | 80.0% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1271 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Laguna XS.2 | MiniMax M2.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.7% | Not comparable |
Frequently Asked Questions (3)
Which is better, Laguna XS.2 or MiniMax M2.7?
Laguna XS.2 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, Laguna XS.2 or MiniMax M2.7?
Laguna XS.2 has the edge for coding in this comparison, averaging 60.8 versus 53.3. Inside this category, SWE Multilingual is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Laguna XS.2 or MiniMax M2.7?
MiniMax M2.7 has the edge for agentic tasks in this comparison, averaging 57 versus 35.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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