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MiniMax M3 vs DeepSeek V4 Pro
DeepSeek V4 Pro scores higher than MiniMax M3 on all 4 public leaderboards that rate both. On the ArtificialWatch Index, which takes the median of each model's percentile across the boards that score it, MiniMax M3 is at 5.1 and DeepSeek V4 Pro at 23.3 (out of 100). On each maker's API, MiniMax M3 costs $0.30 / $1.20 per 1M tokens (input / output) and DeepSeek V4 Pro $0.66 / $1.98.
Scores as published by each board; table composed November 10, 2026.
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Leaderboard by leaderboard
| Board | MiniMax M3 | DeepSeek V4 Pro | Higher |
|---|---|---|---|
| LMArena Elo (community votes) | 1,484.2 | 1,581.2 | DeepSeek V4 Pro |
| SimpleBench AVG@5 % (private set) | 45.8 | 50.9 | DeepSeek V4 Pro |
| Artificial Analysis intelligence index · measured runs only | 18.7 | 23.1 | DeepSeek V4 Pro |
| Epoch AI Epoch Capabilities Index (ECI) · many benchmarks on one scale | 147.8 | 155.9 | DeepSeek V4 Pro |
Raw scores are each board's own scale, so compare within a row, not across rows. Full table: the bench index.
For coding
On the ArtificialWatch coding index, MiniMax M3 is at 16.8 (#44 of 47) and DeepSeek V4 Pro at 39.5 (#27). DeepSeek V4 Pro scores higher on both coding boards that rate them.
| Coding board | MiniMax M3 | DeepSeek V4 Pro |
|---|---|---|
| LMArena · Coding | 1,468.6 | 1,469.3 |
| Vals Vibe Code Bench | 47.6 | 82.3 |
MiniMax M3 at a glance
- Developer
- MiniMax
- Status
- Live since May 31, 2026
- API price
- $0.30 input / $1.20 output per 1M tokens · MiniMax, MiniMax-M3
- Context window
- 1M tokens
Live — $0.30/$1.20 per 1M.
DeepSeek V4 Pro at a glance
- Developer
- DeepSeek
- Status
- Live since April 24, 2026
- API price
- $0.66 input / $1.98 output per 1M tokens · DeepSeek, deepseek-v4-pro
- Context window
- 1.05M tokens
Live · open weights · superseded by V4.1 Flash — per DeepSeek's own changelog rather than our own reading, deepseek-v4-flash routes to V4.1 Flash; the matching deepseek-v4-pro cutover set for 04:00 UTC Sep 14 was reversed on its eve and V4 Pro is still served at unchanged billing, which is search-grade too — but our own bench refresh still scored deepseek-v4-pro-0813 as a separate model on Sep 16 · our sweep read the bare deepseek-flash alias on Sep 10 at $0.15/$0.60 per 1M, 1M ctx.
DeepSeek V4-Pro lands at $0.435/$0.87 — and "model names remain unchanged" hides a 2.7x price fork
2026-08-13 · DeepSeek launched V4-Pro today on app, web and API. The headline features are agent upgrades, selectable reasoning effort across V4-Pro and V4-Flash, and native OpenAI Responses API support optimised for Codex. The line worth reading twice is the quiet one: "Model names remain unchanged."
MiniMax M3 vs DeepSeek V4 Pro: quick answers
Which is better, MiniMax M3 or DeepSeek V4 Pro?
It depends on what you measure. DeepSeek V4 Pro scores higher than MiniMax M3 on all 4 public leaderboards that rate both. DeepSeek V4 Pro's widest lead is on Epoch AI. On the ArtificialWatch Index, which takes the median of each model's percentile across the boards that score it, MiniMax M3 is at 5.1 and DeepSeek V4 Pro at 23.3 (out of 100).
Which is newer, MiniMax M3 or DeepSeek V4 Pro?
MiniMax M3. It went live on May 31, 2026, 37 days after DeepSeek V4 Pro (April 24, 2026).
Which is cheaper, MiniMax M3 or DeepSeek V4 Pro?
MiniMax M3 is cheaper on both input and output. On each vendor's own API, MiniMax M3 is $0.30 input / $1.20 output per million tokens and DeepSeek V4 Pro is $0.66 input / $1.98 output per million tokens. MiniMax M3's rate rises for prompts over 512K tokens. Prices as published in the models.dev catalog, as of 2026-11-10.
Which has the bigger context window, MiniMax M3 or DeepSeek V4 Pro?
DeepSeek V4 Pro, at 1.05M tokens against MiniMax M3's 1M, as each vendor lists it.
How do MiniMax M3 and DeepSeek V4 Pro compare for coding?
On the ArtificialWatch coding index, MiniMax M3 is at 16.8 (#44 of 47) and DeepSeek V4 Pro at 39.5 (#27). DeepSeek V4 Pro scores higher on both coding boards that rate them.
Who makes MiniMax M3 and DeepSeek V4 Pro?
MiniMax M3 is from MiniMax; DeepSeek V4 Pro is from DeepSeek.
Where do these numbers come from?
Each score is the leaderboard's own published figure, read by ArtificialWatch (table composed November 10, 2026). Boards measure different things, so raw scores are only comparable within a row.
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