Benchmark Almanac

Doubao Multi-Turn Bench

GPT-5.5 62.5% leads since June 2026
In use

Models answer the turn of a real Doubao conversation where the user was dissatisfied, with the earlier turns as context. Rubrics grade each answer.

In-house Seed benchmark filtered from online Doubao user conversations.

Made by
ByteDance Seed
Released
June 2026
Kind
Multi-turn conversation
Level
Everyday
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Strongest model tested
GPT-5.5 #20 on the capability index
Last in a launch post
June 2026
Last model added
June 2026
Scores refreshed
November 12th, 2026
1
Model scored in lab cards
1
Launch post lists it, from 1 lab
1
System card reports it, from 1 lab

Seed2.1 Pro leads with 52.5%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

GPT-5.5 leads with 62.5% across all independent runs

Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.

  1. 1 Seed2.1 Pro 52.5%

Source: Labs’ model cards

Source: Official Doubao Multi-Turn Bench leaderboard

#ModelScoreSettingDateSource
1 Seed2.1 Pro 52.5% Jun 2026 Lab model card
#ModelScoreSettingDateSource
1 GPT-5.5 62.5% Apr 2026 Official leaderboard
2 Seed2.1 Pro 52.5% Jun 2026 Official leaderboard
3 Gemini 3.1 Pro 52% Feb 2026 Official leaderboard
4 Claude Opus 4.7 49.8% Apr 2026 Official leaderboard

The benchmark's own leaderboard has 5 entries, 4 of them models we track. Switch the scores above to rank them together.

Number one over time Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release.

OpenAI
Own leaderboard Not tested since Jun 2026
GPT-5.5 62.5%

Source: Official Doubao Multi-Turn Bench leaderboard

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Reported by the lab in its model card Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GPT-5.5 Gemini 3.1 Pro 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GPT-5.5 Gemini 3.1 Pro

Sources: Official Doubao Multi-Turn Bench leaderboard and labs’ model cards

One lab put it in a launch post in the last six months

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

ByteDance Seed
DateLaunch postScoreAs the post writes it
Jun 23, 2026 Seed2.1 Pro 52.5 Doubao Multi-Turn Bench

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Jun 23, 2026 Seed2.1 Pro model card 52.5 Doubao Multi-Turn Bench (Table 2) Capabilities

One lab claim next to the leaderboard

Each score a lab reported for its own model, beside the same model's best score on the leaderboard. Gaps mostly come from different harnesses, effort levels and task subsets. 1 of them match, which usually means one side copied the other. Every benchmark.

Model Lab says Board says Gap
Seed2.1 Pro 52.5% Doubao Multi-Turn Bench 52.5% Leaderboard Same

More in Instructions and chat

All 81 in Instructions and chat
  • IFEval In use Models answer about 500 prompts containing verifiable instructions such as word limits or required keywords. Code checks each instruction for strict and loose accuracy. Gemma 4 31B IT 98.9%
  • IFBench In use 58 new out-of-domain verifiable output constraints. Scored by programmatic constraint checks (strict or loose). Nemotron-Cascade 2 30B-A3B 82.9%
  • MultiChallenge In use Multi-turn conversations testing instruction retention, inference memory, versioned editing and self-coherence. Graded by LLM judge with rubrics. GPT-6.1 Sol 82%
  • Multi-IF In use Models follow verifiable instructions over three-turn conversations in eight languages, extending IFEval. Scored by instruction accuracy at each turn. LFM3-1.7B 89.1%
  • AdvancedIF In use Models respond to over 1,600 prompts with complex, multi-turn, and system-level instructions. A judge model checks each response against expert-written rubrics. MAI-Thinking-1 85%
  • IFStruct In use Models generate JSON or YAML that must follow a requested schema and phrasing constraints, without constrained decoding. A response passes only if every structural constraint holds. Gemma 4 31B IT 95.9%