whatmodel.sh / Seed 2.1 Pro (Preview)
Seed 2.1 Pro (Preview)
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Seed 2.1 Pro (Preview) is a closed-weights language model from ByteDance Seed, released June 2026.
Catalogue identity notes
Comparison-only. Arena entry 'seed-2.1-pro-preview' (webdev). Released 2026-06: ByteDance Seed blog referencing 'Seed2.1 Preview' on Code Arena (June 2026); Seed 2.1 released 2026-06-23. ByteDance publicly named a 'Seed2.1 Preview' evaluated on Code Arena (frontend), matching this webdev entry first listed 2026-06-16, a week before the official Seed 2.1 release; not asserted to equal the released doubao-seed-2-1-pro checkpoints.
$ how it compares
The LLMs ranked either side of Seed 2.1 Pro (Preview), out of 1132 with a score, then more from ByteDance Seed.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 58 |  Gemini 3.6 Flash | 74±1 | api $1.50/M | ||
| 59 |  GLM-5.2 | 74±1 | api $2.15/M +local | ||
| 60 | Seed 2.1 Pro (Preview) | 74±3 | comparison only | ||
| 61 |  Dola Seed 2.0 Pro | 74±2 | comparison only | ||
| 62 |  Qwen3.7 Max Preview | 74±3 | comparison only | ||
| more from ByteDance Seed | |||||
| 66 | Seed2.0 Lite | 73±4 | comparison only | ||
| 235 | Seed-OSS 36B Instruct | 63±1 | local | ||
$ what it's good at
coding▁▁▁▃▅▇█▇▅▄▂▁ #48 of 549 * · 97% of its score · 1 test
Beats GPT-5.4, DeepSeek V4 Flash Vision (Exp), Gemini 3.1 Pro (Preview) here, though they rank higher overall. Trails Mistral Large 4 (public preview), Claude Sonnet 4.6, Qwen3.8 27B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena WebDev (Code Arena) | 1516.9 ✎ | ▁▂▄▃▅█▄▇▆▄▁▁ beats 75/119 | 97% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 97%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 LMArena leaderboard dataset | 1 | 97% |
| prior · pull toward the middle | 3% | |
| weighted average | = 73.6 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json