Model comparison
Inkling vs MiniMax M2.7
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Inkling #17; MiniMax M2.7 unranked
BenchAlign evidence: Inkling not scored; MiniMax M2.7 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Inkling and MiniMax M2.7 share 3 comparable benchmark results. 2 of 8 categories are comparable. 13 results are unique to Inkling; 34 to MiniMax M2.7.
Updated July 15, 2026- Shared results
- 3
- Inkling only
- 13
- MiniMax M2.7 only
- 34
- Comparable categories
- 2 / 8
Pick Inkling if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice 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 3 shared benchmark results across 3 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
Inkling is clearly ahead on the provisional aggregate, 69 to 52. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Inkling's sharpest advantage is in coding, where it averages 68.6 against 53.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.8% to 57%.
Inkling is also the more expensive model on tokens at $1.87 input / $4.68 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 3.9x on output cost alone. MiniMax M2.7 is the reasoning model in the pair, while Inkling 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. Inkling 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 | Inkling | Δ | MiniMax M2.7 |
|---|---|---|---|
| Coding | Inkling68.6 | Margin← 15.3 | MiniMax M2.753.3 |
| Agentic | Inkling69.4 | Margin← 12.4 | MiniMax M2.757.0 |
| Knowledge | Inkling51.7 | MarginNo overlap | MiniMax M2.7Not measured |
| Math | Inkling97.1 | MarginNo overlap | MiniMax M2.7Not measured |
| Multimodal | Inkling76.5 | MarginNo overlap | MiniMax M2.7Not measured |
| Inst. Following | Inkling79.8 | 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 63.8%B 57%Winner: InklingΔ 6.8Terminal-Bench 2.0: Inkling scored 63.8%; MiniMax M2.7 scored 57%. Inkling wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 54.3%B 56.2%Winner: MiniMax M2.7Δ 1.9SWE-bench Pro: Inkling scored 54.3%; 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 | Inkling | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Inkling$1.87 input / $4.68 output | MiniMax M2.7$0.3 input / $1.2 output | MiniMax M2.7 has the lower combined listed price. |
| Generation speedtokens per second | InklingNot available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | InklingNot available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Inkling1M | MiniMax M2.7200K | Inkling lists the larger context window. |
Benchmark Deep Dive
AgenticInkling wins14 benchmarks
| Benchmark | Inkling | MiniMax M2.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.8% | 57% | Inkling leads |
| BrowseCompSource | 77.1% | — | Not comparable |
| MCP AtlasSource | 74.1% | — | Not comparable |
| Design Arena Agentic Web DevSource | 1258 | — | 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 |
| AA Agentic IndexSource | — | 25.6% | Not comparable |
| APEX-Agents-AASource | — | 10.6% | Not comparable |
| GDPval-AASource | — | 32.9% | Not comparable |
| GDPval-AASource | — | 1158 | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
CodingInkling wins14 benchmarks
| Benchmark | Inkling | MiniMax M2.7 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.6% | — | Not comparable |
| SWE-bench ProSource | 54.3% | 56.2% | MiniMax M2.7 leads |
| Terminal-Bench 2.0Source | 63.8% | — | Not comparable |
| 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 |
| AA Coding IndexSource | — | 52.6% | Not comparable |
| Terminal-Bench HardSource | — | 39.4% | Not comparable |
| AA-SciCodeSource | — | 47.0% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Inkling | MiniMax M2.7 | Result |
|---|---|---|---|
| GPQASource | 87.9% | — | Not comparable |
| GPQA-DSource | 87.9% | 87.0% | Inkling leads |
| HLESource | 46% | — | Not comparable |
| HLE w/o toolsSource | 30% | — | 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 |
Math2 benchmarks
Multimodal5 benchmarks
Frequently Asked Questions (3)
Which is better, Inkling or MiniMax M2.7?
Inkling is ahead on BenchLM's provisional leaderboard, 69 to 52. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.8% and 57%.
Which is better for coding, Inkling or MiniMax M2.7?
Inkling has the edge for coding in this comparison, averaging 68.6 versus 53.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Inkling or MiniMax M2.7?
Inkling has the edge for agentic tasks in this comparison, averaging 69.4 versus 57. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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