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DeepSeek V4 Pro vs Claude Fable 5
Claude Fable 5 scores higher than DeepSeek V4 Pro on both public leaderboards that rate them. 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 Claude Fable 5 at 60.4 (out of 100). On each maker's API, DeepSeek V4 Pro costs $0.66 / $1.98 per 1M tokens (input / output) and Claude Fable 5 $10 / $50.
Scores as published by each board; table composed November 8, 2026.
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Leaderboard by leaderboard
| Board | DeepSeek V4 Pro | Claude Fable 5 | Higher |
|---|---|---|---|
| LMArena Elo (community votes) | 1,581.6 | 1,625 | Claude Fable 5 |
| SimpleBench AVG@5 % (private set) | 50.9 | 81.9 | Claude Fable 5 |
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 Claude Fable 5 at 88.1 (#5). Claude Fable 5 scores higher on both coding boards that rate them.
| Coding board | DeepSeek V4 Pro | Claude Fable 5 |
|---|---|---|
| LMArena · Coding | 1,469.1 | 1,518.7 |
| Vals Vibe Code Bench | 82.3 | 90.4 |
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Live · open weights · superseded by V4.1 Flash — per DeepSeek's own changelog rather than our own reading, deepseek-v4-flash routes to V4.1 Flash; the matching deepseek-v4-pro cutover set for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."
Claude Fable 5 at a glance
- Developer
- Anthropic
- Status
- Live since July 1, 2026
- API price
- $10 input / $50 output per 1M tokens · Anthropic, claude-fable-5
- Context window
- 1M tokens
Returned Jul 1.
DeepSeek V4 Pro vs Claude Fable 5: quick answers
Which is better, DeepSeek V4 Pro or Claude Fable 5?
It depends on what you measure. Claude Fable 5 scores higher than DeepSeek V4 Pro on both public leaderboards that rate them. Claude Fable 5's widest lead is on SimpleBench. 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 Claude Fable 5 at 60.4 (out of 100).
Which is newer, DeepSeek V4 Pro or Claude Fable 5?
Claude Fable 5. It went live on July 1, 2026, 68 days after DeepSeek V4 Pro (April 24, 2026).
Which is cheaper, DeepSeek V4 Pro or Claude Fable 5?
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 Claude Fable 5 is $10 input / $50 output per million tokens. Prices as published in the models.dev catalog, as of 2026-11-08.
Which has the bigger context window, DeepSeek V4 Pro or Claude Fable 5?
DeepSeek V4 Pro, at 1.05M tokens against Claude Fable 5's 1M, as each vendor lists it.
How do DeepSeek V4 Pro and Claude Fable 5 compare for coding?
On the ArtificialWatch coding index, DeepSeek V4 Pro is at 40 (#27 of 45) and Claude Fable 5 at 88.1 (#5). Claude Fable 5 scores higher on both coding boards that rate them.
Who makes DeepSeek V4 Pro and Claude Fable 5?
DeepSeek V4 Pro is from DeepSeek; Claude Fable 5 is from Anthropic.
Where do these numbers come from?
Each score is the leaderboard's own published figure, read by ArtificialWatch (table composed November 8, 2026). Boards measure different things, so raw scores are only comparable within a row.
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