Skip to main content

Model comparison

GPT-5.4 Pro vs MiniMax M2.7

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

60.89/100
Margin
3.2pts
winning →
64.11/100
1 category wins0 category wins

Public leaderboard positions: GPT-5.4 Pro #44 (Estimated); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.4 Pro and MiniMax M2.7 share 1 comparable benchmark result. 1 of 8 categories are comparable. 11 results are unique to GPT-5.4 Pro; 34 to MiniMax M2.7.

Updated July 23, 2026
Shared results
1
GPT-5.4 Pro only
11
MiniMax M2.7 only
34
Comparable categories
1 / 8

Pick MiniMax M2.7 if you want the stronger benchmark profile. GPT-5.4 Pro only becomes the better choice if agentic is the priority or you need the larger 1.05M context window.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

MiniMax M2.7 is clearly ahead on the BenchAlign aggregate, 64.11 to 60.89. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.4 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 150.0x on output cost alone. GPT-5.4 Pro 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 Pro 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 Pro and MiniMax M2.7
CategoryGPT-5.4 ProΔMiniMax M2.7
AgenticGPT-5.4 Pro89.3Margin 32.3MiniMax M2.757.0
CodingGPT-5.4 ProNot measuredMarginNo overlapMiniMax M2.753.3
ReasoningGPT-5.4 Pro83.3MarginNo overlapMiniMax M2.7Not measured
KnowledgeGPT-5.4 Pro58.7MarginNo overlapMiniMax M2.7Not measured
MathGPT-5.4 Pro46.9MarginNo overlapMiniMax M2.7Not measured
MultimodalGPT-5.4 Pro94.0MarginNo overlapMiniMax M2.7Not measured

Operational comparison

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

MetricGPT-5.4 ProMiniMax M2.7Comparison
Input / output priceUSD per 1M tokensGPT-5.4 Pro$30 input / $180 outputMiniMax M2.7$0.3 input / $1.2 outputMiniMax M2.7 has the lower combined listed price.
Generation speedtokens per secondGPT-5.4 Pro74 tok/sMiniMax M2.745 tok/sGPT-5.4 Pro has the higher measured throughput.
First-answer latencyseconds to first tokenGPT-5.4 Pro151.79 sMiniMax M2.72.53 sMiniMax M2.7 reaches the first token sooner.
Context windowmaximum listed tokensGPT-5.4 Pro1.05MMiniMax M2.7200KGPT-5.4 Pro lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.4 Pro wins
BenchmarkGPT-5.4 ProMiniMax M2.7Result
BrowseCompSource 89.3%Not comparable
Terminal-Bench 2.0Source 57%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 1158Not comparable
Gert LabsSource 40.40%Not comparable
Coding
BenchmarkGPT-5.4 ProMiniMax M2.7Result
SWE-bench Verified*Source 75.4%Not comparable
SWE-bench ProSource 56.2%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
AA-SciCodeSource 47.0%Not comparable
Reasoning
BenchmarkGPT-5.4 ProMiniMax M2.7Result
ARC-AGI-2Source 83.3%Not comparable
CritPtSource 30.0%0.6%GPT-5.4 Pro leads
AA-LCRSource 68.7%Not comparable
Knowledge
BenchmarkGPT-5.4 ProMiniMax M2.7Result
HLESource 58.7%Not comparable
FrontierScienceSource 36.7%Not comparable
FrontierScience ResearchSource 36.7%Not comparable
HLE w/o toolsSource 42.7%Not comparable
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
Math
BenchmarkGPT-5.4 ProMiniMax M2.7Result
IPhO 2025 (Theory)Source 93.5%Not comparable
FrontierMath (legacy)Source 50%Not comparable
FrontierMath v2 (Tiers 1-3)Source 50.000%Not comparable
FrontierMath v2 (Tier 4)Source 37.500%Not comparable
AIME25 (Arcee)Source 80.0%Not comparable
Multimodal
BenchmarkGPT-5.4 ProMiniMax M2.7Result
MMMU-ProSource 94%Not comparable
Design Arena WebsiteSource 1275Not comparable
Inst. Following
BenchmarkGPT-5.4 ProMiniMax M2.7Result
AA-IFBenchSource 75.7%Not comparable
Frequently Asked Questions (2)

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

MiniMax M2.7 is ahead on BenchLM's BenchAlign leaderboard, 64.11 to 60.89.

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

GPT-5.4 Pro has the edge for agentic tasks in this comparison, averaging 89.3 versus 57. MiniMax M2.7 stays close enough that the answer can still flip depending on your workload.

Related Comparisons

Last updated: July 23, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.