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Model comparison

GPT-5.4 vs MiniMax M2.7

Data verified

Head-to-head evidence from 25 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

OpenAI
74.24/100
Margin
10.1pts
← winning
64.11/100
2 category wins0 category wins

Public leaderboard positions: GPT-5.4 #8 (Supported); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.4 and MiniMax M2.7 share 25 comparable benchmark results. 2 of 8 categories are comparable. 27 results are unique to GPT-5.4; 10 to MiniMax M2.7.

Updated July 23, 2026
Shared results
25
GPT-5.4 only
27
MiniMax M2.7 only
10
Comparable categories
2 / 8

Pick GPT-5.4 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 25 shared benchmark results across 6 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

GPT-5.4 is clearly ahead on the BenchAlign aggregate, 74.24 to 64.11. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.4's sharpest advantage is in agentic, where it averages 77.2 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 75.1% to 57%.

GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 12.5x on output cost alone. GPT-5.4 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. GPT-5.4 gives you the larger context window at 1.05M, 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 scores and score margins for GPT-5.4 and MiniMax M2.7
CategoryGPT-5.4ΔMiniMax M2.7
AgenticGPT-5.477.2Margin 20.2MiniMax M2.757.0
CodingGPT-5.457.7Margin 4.4MiniMax M2.753.3
KnowledgeGPT-5.457.6MarginNo overlapMiniMax M2.7Not measured
MathGPT-5.442.5MarginNo overlapMiniMax M2.7Not measured
MultimodalGPT-5.473.2MarginNo overlapMiniMax M2.7Not measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · GPT-5.4B · MiniMax M2.7
  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 75.1%B 57%
    Winner: GPT-5.4Δ 18.1
    Terminal-Bench 2.0: GPT-5.4 scored 75.1%; MiniMax M2.7 scored 57%. GPT-5.4 wins this benchmark.
  2. SWE-bench Pro

    Coding
    Source ↗
    A 57.7%B 56.2%
    Winner: GPT-5.4Δ 1.5
    SWE-bench Pro: GPT-5.4 scored 57.7%; MiniMax M2.7 scored 56.2%. GPT-5.4 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGPT-5.4MiniMax M2.7Comparison
Input / output priceUSD per 1M tokensGPT-5.4$2.5 input / $15 outputMiniMax M2.7$0.3 input / $1.2 outputMiniMax M2.7 has the lower combined listed price.
Generation speedtokens per secondGPT-5.474 tok/sMiniMax M2.745 tok/sGPT-5.4 has the higher measured throughput.
First-answer latencyseconds to first tokenGPT-5.4151.79 sMiniMax M2.72.53 sMiniMax M2.7 reaches the first token sooner.
Context windowmaximum listed tokensGPT-5.41.05MMiniMax M2.7200KGPT-5.4 lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.4 wins
BenchmarkGPT-5.4MiniMax M2.7Result
Terminal-Bench 2.0Source 75.1%57%GPT-5.4 leads
CyberGymSource 79.0%Not comparable
BrowseCompSource 82.7%Not comparable
OSWorld-VerifiedSource 75%Not comparable
MCP AtlasSource 70.6%Not comparable
ToolathlonSource 54.6%46.3%GPT-5.4 leads
τ²-bench resultsSource 87.1%84.8%GPT-5.4 leads
Claw-EvalSource 60.3%48.7%GPT-5.4 leads
DeepSearchQASource 73.6%Not comparable
AA Agentic IndexSource 41.1%25.6%GPT-5.4 leads
APEX-Agents-AASource 33.3%10.6%GPT-5.4 leads
GDPval-AASource 44.7%32.9%GPT-5.4 leads
GDPval-AASource 13951158GPT-5.4 leads
Gert LabsSource 64.89%40.40%GPT-5.4 leads
ResearchClawBenchSource 15.3%Not comparable
JobBenchSource 38.9%Not comparable
ExploitGymSource 6.0%Not comparable
MLE-Bench LiteSource 66.6%Not comparable
MM-ClawBenchSource 62.7%Not comparable
CodingGPT-5.4 wins
BenchmarkGPT-5.4MiniMax M2.7Result
LiveCodeBench ProSource 87.5%Not comparable
SWE-bench ProSource 57.7%56.2%GPT-5.4 leads
React Native EvalsSource 85.3%71.4%GPT-5.4 leads
Vibe Code BenchSource 67.42%27.04%GPT-5.4 leads
AA Coding IndexSource 71.0%52.6%GPT-5.4 leads
AA-SciCodeSource 56.6%47.0%GPT-5.4 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
Reasoning
BenchmarkGPT-5.4MiniMax M2.7Result
AA-LCRSource 74.0%68.7%GPT-5.4 leads
CritPtSource 23.4%0.6%GPT-5.4 leads
Knowledge
BenchmarkGPT-5.4MiniMax M2.7Result
GPQASource 92.8%Not comparable
HLESource 52.1%Not comparable
HLE w/o toolsSource 39.8%Not comparable
GPQA-DSource 92.8%87.0%GPT-5.4 leads
HealthBench HardSource 40.1%Not comparable
MedXpertQA (Text)Source 59.6%Not comparable
Artificial Analysis Intelligence IndexSource 51.4%38.1%GPT-5.4 leads
AA-GPQA DiamondSource 92.0%87.4%GPT-5.4 leads
AA-HLESource 41.6%28.1%GPT-5.4 leads
AA-Omniscience IndexSource 5.7%0.7%GPT-5.4 leads
AA-Omniscience AccuracySource 50.0%26.1%GPT-5.4 leads
AA-Omniscience Hallucination RateSource 88.6%34.4%MiniMax M2.7 leads
HealthBench ProfessionalSource 48.1%Not comparable
MMLU-Pro (Arcee)Source 80.8%Not comparable
Math
BenchmarkGPT-5.4MiniMax M2.7Result
FrontierMath v2 (Tiers 1-3)Source 47.600%Not comparable
FrontierMath v2 (Tier 4)Source 27.100%Not comparable
AIME25 (Arcee)Source 80.0%Not comparable
Multimodal
BenchmarkGPT-5.4MiniMax M2.7Result
MMMU-ProSource 81.2%Not comparable
OfficeQA ProSource 53.2%Not comparable
MMMU-Pro w/ PythonSource 82.1%Not comparable
CharXivSource 82.8%Not comparable
ERQASource 65.4%Not comparable
SimpleVQASource 61.1%Not comparable
ScreenSpot ProSource 85.4%Not comparable
ZeroBenchSource 41.0%Not comparable
MedXpertQA (MM)Source 77.1%Not comparable
AA-MMMU-ProSource 78.4%Not comparable
Design Arena WebsiteSource 12501275MiniMax M2.7 leads
Inst. Following
BenchmarkGPT-5.4MiniMax M2.7Result
AA-IFBenchSource 73.9%75.7%MiniMax M2.7 leads
Frequently Asked Questions (3)

Which is better, GPT-5.4 or MiniMax M2.7?

GPT-5.4 is ahead on BenchLM's BenchAlign leaderboard, 74.24 to 64.11. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 75.1% and 57%.

Which is better for coding, GPT-5.4 or MiniMax M2.7?

GPT-5.4 has the edge for coding in this comparison, averaging 57.7 versus 53.3. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GPT-5.4 or MiniMax M2.7?

GPT-5.4 has the edge for agentic tasks in this comparison, averaging 77.2 versus 57. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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