MiniMax M3.1 Flash in practice: tests and comparisons with DeepSeek V4.1 Flash

SandBase Lab ran the same Orbital Atlas Skill through MiniMax M3.1 Flash and DeepSeek V4.1 Flash and shows the two solar-system builds side by side.

A write-up of M3.1 Flash specs and benchmark gaps, noting it answered 41 of 43 Plotly data-analysis questions but ran slower and cost more than the preview, plus weights and access.

Roundup of official specs and Artificial Analysis results: Intelligence Index 42 (up from 29), 48% on Humanity's Last Exam, ~$0.22 per task versus DeepSeek V4.1 Flash's 45, plus a noted tendency to answer wrongly instead of admitting uncertainty.

On the same hardware device launch landing page prompt, MiniMax M3.1 Flash cost $0.014 versus Claude Opus 5.5's $1.22, with the author claiming 88x cheaper, 4x faster and better token efficiency.

A Halloween continuous-3D-scene prompt in Atomic Agent had local Qwen 3.8 27B write the plan and M3.1 Flash do the coding, finishing in 8 minutes, with the author reporting a 1.5x speedup for M3.1 Flash in the tool.

The author pairs Opus 5.5 for planning with MiniMax M3.1 Flash for execution inside the Claude Code harness.

The author argues the 'open models are 10x cheaper' claim no longer holds: cost per task is $0.21 for Haiku 5.5, $0.22 for M3.1 Flash and $0.28 for GLM-5.3-Flash, and notes M3.1 Flash has a 93% hallucination rate on AA-Omniscience.

On the same "Golden Desert Oasis" prompt, DeepSeek V4.1 Flash passed on its second try in 21.9s, while MiniMax M3.1 Flash's free tier passed in one shot but took 576.8s — 26x slower.

On the same three-bears jelly prompt, M3.1 Flash cost $1.43 in 1h20m with 4.5k tokens versus Opus 5.5's $7, 2h10m and 6k tokens, with similar results at nearly 5x lower cost.

MiniMax's official account cites Parallel Web System data showing M3.1 Flash ranked first on the search-capability efficiency leaderboard, emphasizing its speed.

Hands-on test has M3.1 Flash build an explainer site with isometric drawings of a Rubik's cube, pencil sharpener and spring-lever espresso machine, auto and manual step modes, live counters and captions; the author cites 73.7% on DeepSWE at under $0.50 per task.

The author argues the $0.15/$0.60/$0.015 per-million input, output and cached-input pricing matters more than 74% on DeepSWE, wants cost per successfully completed task including retries, and looks forward to open weights on October 23.