DeepSeek V3.2 vs MiniMax M2.7

Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.

DeepSeek V3.2 finishes one point ahead overall, 58 to 57. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.

DeepSeek V3.2's sharpest advantage is in agentic, where it averages 58.8 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 60% to 57%. MiniMax M2.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

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 DeepSeek V3.2. That is roughly Infinityx on output cost alone. MiniMax M2.7 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.2.

Quick Verdict

Pick DeepSeek V3.2 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if coding is the priority or you need the larger 200K context window.

Agentic

DeepSeek V3.2

DeepSeek V3.2

58.8

MiniMax M2.7

57

60%
Terminal-Bench 2.0
57%
62%
BrowseComp
Coming soon
55%
OSWorld-Verified
Coming soon
Coming soon
Toolathlon
46.3%
Coming soon
MLE-Bench Lite
66.6%
Coming soon
MM-ClawBench
62.7%

Coding

MiniMax M2.7

DeepSeek V3.2

40.6

MiniMax M2.7

56.2

76%
HumanEval
Coming soon
45%
SWE-bench Verified
Coming soon
39%
LiveCodeBench
Coming soon
Coming soon
SWE-bench Pro
56.2%
Coming soon
SWE Multilingual
76.5%
Coming soon
Multi-SWE Bench
52.7%
Coming soon
VIBE-Pro
55.6%
Coming soon
NL2Repo
39.8%

Multimodal & Grounded

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

72%
OfficeQA Pro
Coming soon
Coming soon
GDPval-AA
1495

Reasoning

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

79%
MuSR
Coming soon
81%
BBH
Coming soon
69%
LongBench v2
Coming soon
70%
MRCRv2
Coming soon
4%
ARC-AGI-2
Coming soon

Knowledge

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

84%
MMLU
Coming soon
83%
GPQA
Coming soon
81%
SuperGPQA
Coming soon
11%
HLE
Coming soon
72%
FrontierScience
Coming soon
81%
SimpleQA
Coming soon
Coming soon
Artificial Analysis
50

Instruction Following

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

85%
IFEval
Coming soon

Multilingual

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

84%
MGSM
Coming soon
81%
MMLU-ProX
Coming soon

Mathematics

Coming soon

Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.

84%
AIME 2023
Coming soon
86%
AIME 2024
Coming soon
85%
AIME 2025
Coming soon
80%
HMMT Feb 2023
Coming soon
82%
HMMT Feb 2024
Coming soon
81%
HMMT Feb 2025
Coming soon
83%
BRUMO 2025
Coming soon
81%
MATH-500
Coming soon

Frequently Asked Questions

Which is better, DeepSeek V3.2 or MiniMax M2.7?

DeepSeek V3.2 is ahead overall, 58 to 57. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 60% and 57%.

Which is better for coding, DeepSeek V3.2 or MiniMax M2.7?

MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 40.6. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, DeepSeek V3.2 or MiniMax M2.7?

DeepSeek V3.2 has the edge for agentic tasks in this comparison, averaging 58.8 versus 57. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Last updated: March 18, 2026

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