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DeepSeek V4 Pro vs Kimi K3
Of the 3 public leaderboards that rate both, DeepSeek V4 Pro scores higher on 1 and Kimi K3 on 2. On the ArtificialWatch Index, which takes the median of each model's percentile across the boards that score it, DeepSeek V4 Pro is at 19.9 and Kimi K3 at 27.1 (out of 100). On each maker's API, DeepSeek V4 Pro costs $0.66 / $1.98 per 1M tokens (input / output) and Kimi K3 $3 / $15.
Scores as published by each board; table composed November 7, 2026.
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Leaderboard by leaderboard
| Board | DeepSeek V4 Pro | Kimi K3 | Higher |
|---|---|---|---|
| LMArena Elo (community votes) | 1,581.6 | 1,656.5 | Kimi K3 |
| SimpleBench AVG@5 % (private set) | 50.9 | 60.7 | Kimi K3 |
| Vals AI Vals Index accuracy % · weighted finance + coding tasks | 53 | 53 | 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, DeepSeek V4 Pro is at 40 (#27 of 45) and Kimi K3 at 66 (#16). Kimi K3 scores higher on both coding boards that rate them.
| Coding board | DeepSeek V4 Pro | Kimi K3 |
|---|---|---|
| LMArena · Coding | 1,469.1 | 1,506.5 |
| Vals Vibe Code Bench | 82.3 | 85 |
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Live · open weights · superseded by V4.1 Flash — per DeepSeek's own changelog rather than our own reading, deepseek-v4-flash routes to V4.1 Flash; the matching deepseek-v4-pro cutover set for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."
Kimi K3 at a glance
- Developer
- Moonshot
- Status
- Live since July 15, 2026
- API price
- $3 input / $15 output per 1M tokens · Moonshot AI, kimi-k3
- Context window
- 1.05M tokens
Live — dropped Jul 15 · 2.8T · open weights landed Jul 27 (1.56 TB, MXFP4).
Kimi K3, day one: impressive, expensive, and a little slow
2026-07-16 · Kimi K3 has been live for a day, and the picture forming is more interesting than the launch-night hype. Here's everything we're seeing so far.
DeepSeek V4 Pro vs Kimi K3: quick answers
Which is better, DeepSeek V4 Pro or Kimi K3?
It depends on what you measure. Of the 3 public leaderboards that rate both, DeepSeek V4 Pro scores higher on 1 and Kimi K3 on 2. DeepSeek V4 Pro's widest lead is on Vals AI; Kimi K3's widest lead is on LMArena. On the ArtificialWatch Index, which takes the median of each model's percentile across the boards that score it, DeepSeek V4 Pro is at 19.9 and Kimi K3 at 27.1 (out of 100).
Which is newer, DeepSeek V4 Pro or Kimi K3?
Kimi K3. It went live on July 15, 2026, 82 days after DeepSeek V4 Pro (April 24, 2026).
Which is cheaper, DeepSeek V4 Pro or Kimi K3?
DeepSeek V4 Pro is cheaper on both input and output. On each vendor's own API, DeepSeek V4 Pro is $0.66 input / $1.98 output per million tokens and Kimi K3 is $3 input / $15 output per million tokens. Prices as published in the models.dev catalog, as of 2026-11-07.
Which has the bigger context window, DeepSeek V4 Pro or Kimi K3?
Neither. Both take 1.05M tokens.
How do DeepSeek V4 Pro and Kimi K3 compare for coding?
On the ArtificialWatch coding index, DeepSeek V4 Pro is at 40 (#27 of 45) and Kimi K3 at 66 (#16). Kimi K3 scores higher on both coding boards that rate them.
Who makes DeepSeek V4 Pro and Kimi K3?
DeepSeek V4 Pro is from DeepSeek; Kimi K3 is from Moonshot.
Where do these numbers come from?
Each score is the leaderboard's own published figure, read by ArtificialWatch (table composed November 7, 2026). Boards measure different things, so raw scores are only comparable within a row.
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