MultiChallenge
Multi-turn conversations testing instruction retention, inference memory, versioned editing and self-coherence. Graded by LLM judge with rubrics.
On February 3rd, 2026 Scale switched the judge to Gemini 2.5 Pro and rewrote the rubric questions of 54 tasks. Scores published before that date may not match the current board.
- Made by
- Scale AI
- Released
- January 2025
- Kind
- Multi-turn conversation
- Level
- Everyday
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Public, plus a private test set
- Strongest model tested
- GPT-6.1 Sol #5 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
We present MultiChallenge, a pioneering benchmark evaluating large language models (LLMs) on conducting multi-turn conversations with human users, a crucial yet underexamined capability for their applications. MultiChallenge identifies four categories of challenges in multi-turn conversations that are not only common and realistic among current human-LLM interactions, but are also challenging to all current frontier LLMs. All 4 challenges require accurate instruction-following, context allocation, and in-context reasoning at the same time. We also develop LLM as judge with instance-level rubrics to facilitate an automatic evaluation method with fair agreement with experienced human raters. Despite achieving near-perfect scores on existing multi-turn evaluation benchmarks, all frontier models have less than 50% accuracy on MultiChallenge, with the top-performing Claude 3.5 Sonnet (June 2024) achieving just a 41.4% average accuracy.
GPT-6.1 Sol leads with 82%
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
GPT-6.1 Sol leads with 82%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
- 82.0 GPT-6.1 Sol
- 78.7
Gemini 4 Argon
- 75.5
Muse Spark
- 75.3
Muse Spark 1.1
- 74.9
DeepSeek V4.1 Flash 1017
- 74.2
Muse Spark Open
- 74.2 GPT-6.1 Terra
- 71.4
Gemini 3.1 Pro
- 69.2 GPT-5.4 Pro
- 67.7 Claude Haiku 5.5
- 65.7
Gemini 3 Pro
- 63.4 GPT-5.1
- 63.2 GPT-5
- 62.4 o3-pro
- 61.4 Kimi K2.5
- 60.6
Gemini 3.1 Flash-Lite
- 59.0 GPT-5 mini
- 59.0 Claude Opus 4.5
- 58.6 Claude Opus 4
- 57.2 Claude Opus 4.1
- 57.1 Claude Sonnet 4
- 56.6 o3
- 56.0
Nemotron 3.5 Bolt E4B
- 56.0 Claude Opus 4.6
- 55.4 Kimi K2 Thinking
- 55.3 Claude Sonnet 4.5
- 53.6
Gemini 2.5 Pro
- 51.6 Claude 3.7 Sonnet
- 51.2 GPT-5.1 Instant
- 50.5 Claude Haiku 4.5
- 46.1
DeepSeek-V3.1
- 45.3 gpt-oss-120b
- 44.9 o4-mini
- 43.2
Gemma 4 E4B
- 41.2
Qwen3-235B-A22B
- 39.4 GPT-4.1
- 38.7
Nemotron 3 Nano 4B
- 36.4
Gemini 2.0 Flash
- 36.0
Gemma 4 E2B
- 27.8 Ministral 3 8B
- 25.7 Ministral 3 3B
- 25.1
Qwen3.5-4B
- 23.7
Llama 3.1-8B
- 22.8
Gemma 3 4B
- 1 GPT-6.1 Sol 82%
- 2
Gemini 4 Argon 78.7%
- 3
Muse Spark 75.5%
- 4
Muse Spark 1.1 75.3%
- 5
DeepSeek V4.1 Flash 1017 74.9%
- 6
Muse Spark Open 74.2%
- 7 GPT-6.1 Terra 74.2%
- 8
Gemini 3.1 Pro 71.4%
- 9 GPT-5.4 Pro 69.2%
- 10 Claude Haiku 5.5 67.7%
- 11
Gemini 3 Pro 65.7%
- 12 GPT-5.1 thinking 63.4%
- 13 GPT-5 thinking 63.2%
- 14 o3-pro high 62.4%
- 15 Kimi K2.5 61.4%
- 16
Gemini 3.1 Flash-Lite 60.6%
- 17 GPT-5 mini thinking 59%
- 18 Claude Opus 4.5 thinking 59%
- 19 Claude Opus 4 thinking 58.6%
- 20 Claude Opus 4.1 thinking 57.2%
- 21 Claude Sonnet 4 thinking 57.1%
- 22 o3 high 56.6%
- 23
Nemotron 3.5 Bolt E4B thinking 56%
- 24 Claude Opus 4.6 non-thinking 56%
- 25 Kimi K2 Thinking 55.4%
- 26 Claude Sonnet 4.5 thinking 55.3%
- 27
Gemini 2.5 Pro Jun 2025 53.6%
- 28 Claude 3.7 Sonnet thinking 51.6%
- 29 GPT-5.1 Instant 51.2%
- 30 Claude Haiku 4.5 thinking 50.5%
- 31
DeepSeek-V3.1 46.1%
- 32 gpt-oss-120b 45.3%
- 33 o4-mini high 44.9%
- 34
Gemma 4 E4B thinking 43.2%
- 35
Qwen3-235B-A22B 41.2%
- 36 GPT-4.1 39.4%
- 37
Nemotron 3 Nano 4B thinking 38.7%
- 38
Gemini 2.0 Flash Feb 2025 36.4%
- 39
Gemma 4 E2B thinking 36%
- 40 Ministral 3 8B thinking 27.8%
- 41 Ministral 3 3B thinking 25.7%
- 42
Qwen3.5-4B thinking 25.1%
- 43
Llama 3.1-8B 23.7%
- 44
Gemma 3 4B 22.8%
Source: Official MultiChallenge leaderboard
- 82.0 GPT-6.1 Sol
- 78.7
Gemini 4 Argon
- 77.7
Nova 2.0 Pro Preview
- 76.6
Nova 2 Lite
- 75.5
Muse Spark
- 75.5
Nova 2 Omni Preview
- 75.3
Muse Spark 1.1
- 74.9
DeepSeek V4.1 Flash 1017
- 74.2
Muse Spark Open
- 74.2 GPT-6.1 Terra
- 71.4
Gemini 3.1 Pro
- 69.9
Seed2.0 Lite (0428)
- 69.8
Ling-3.1-flash
- 69.6 GPT-5
- 69.2 GPT-5.4 Pro
- 68.3
Seed2.0 Pro
- 67.7 Claude Haiku 5.5
- 67.6
Qwen3.5 397B-A17B
- 66.7
Seed1.8
- 66.0
ERNIE 5.0
- 65.7
Gemini 3 Pro
- 64.8 GLM-5
- 63.8
Nemotron 3 Ultra
- 63.4 GPT-5.1
- 63.3
Qwen3-Max
- 62.6
STEP3-VL-10B
- 62.6
Tencent HY 2.0 Think
- 62.4 o3-pro
- 62.3 GPT-5 mini
- 61.5
Qwen3.5-122B-A10B
- 61.4 Kimi K2.5
- 61.0
Solar Open 2
- 60.8
Qwen3.5-27B
- 60.6
Gemini 3.1 Flash-Lite
- 60.4 Mercury 3
- 60.0
Qwen3.5-35B-A3B
- 59.0 Claude Opus 4.5
- 58.6 Claude Opus 4
- 57.2 Claude Opus 4.1
- 57.1 Claude Sonnet 4
- 56.6 o3
- 56.0
Nemotron 3.5 Bolt E4B
- 56.0 Claude Opus 4.6
- 55.7
Step 3.5 Flash
- 55.4 Kimi K2 Thinking
- 55.3 Claude Sonnet 4.5
- 55.2
Nemotron 3 Super
- 54.9 GPT-5 nano
- 54.5
Qwen3.5-9B
- 54.1 Kimi K2
- 53.6
Gemini 2.5 Pro
- 53.0
MAI-Thinking-1
- 52.8 GLM-4.5
- 51.6 Claude 3.7 Sonnet
- 51.2 GPT-5.1 Instant
- 50.9
Ring-1T
- 50.5 Claude Haiku 4.5
- 49.0
Qwen3.5-4B
- 46.1
DeepSeek-V3.1
- 45.3 gpt-oss-120b
- 45.3
Nemotron-Cascade 2 30B-A3B
- 44.9 o4-mini
- 44.7
MiniMax-M1-80k
- 43.2
Gemma 4 E4B
- 42.5 GLM-4.5-Air
- 41.2
Qwen3-235B-A22B
- 39.4 GPT-4.1
- 38.7
Nemotron 3 Nano 4B
- 38.5
Nemotron 3 Nano 30B-A3B
- 36.4
Gemini 2.0 Flash
- 36.0
Gemma 4 E2B
- 35.8 GPT-4.1 mini
- 33.7
Qwen3.5-2B
- 23.7
Llama 3.1-8B
- 22.8
Gemma 3 4B
- 18.9
Qwen3.5-0.8B
- 15.0 GPT-4.1 nano
- 1 GPT-6.1 Sol 82%
- 2
Gemini 4 Argon 78.7%
- 3
Nova 2.0 Pro Preview 77.7%
- 4
Nova 2 Lite 76.6%
- 5
Muse Spark 75.5%
- 6
Nova 2 Omni Preview 75.5%
- 7
Muse Spark 1.1 75.3%
- 8
DeepSeek V4.1 Flash 1017 74.9%
- 9
Muse Spark Open 74.2%
- 10 GPT-6.1 Terra 74.2%
- 11
Gemini 3.1 Pro 71.4%
- 12
Seed2.0 Lite (0428) 69.9%
- 13
Ling-3.1-flash 69.8%
- 14 GPT-5 69.6%
- 15 GPT-5.4 Pro 69.2%
- 16
Seed2.0 Pro 68.3%
- 17 Claude Haiku 5.5 67.7%
- 18
Qwen3.5 397B-A17B 67.6%
- 19
Seed1.8 66.7%
- 20
ERNIE 5.0 66%
- 21
Gemini 3 Pro 65.7%
- 22 GLM-5 64.8%
- 23
Nemotron 3 Ultra 63.8%
- 24 GPT-5.1 thinking 63.4%
- 25
Qwen3-Max 63.3%
- 26
STEP3-VL-10B 62.6%
- 27
Tencent HY 2.0 Think 62.6%
- 28 o3-pro high 62.4%
- 29 GPT-5 mini 62.3%
- 30
Qwen3.5-122B-A10B 61.5%
- 31 Kimi K2.5 61.4%
- 32
Solar Open 2 61%
- 33
Qwen3.5-27B 60.8%
- 34
Gemini 3.1 Flash-Lite 60.6%
- 35 Mercury 3 60.4%
- 36
Qwen3.5-35B-A3B 60%
- 37 Claude Opus 4.5 thinking 59%
- 38 Claude Opus 4 thinking 58.6%
- 39 Claude Opus 4.1 thinking 57.2%
- 40 Claude Sonnet 4 thinking 57.1%
- 41 o3 high 56.6%
- 42
Nemotron 3.5 Bolt E4B thinking 56%
- 43 Claude Opus 4.6 non-thinking 56%
- 44
Step 3.5 Flash 55.7%
- 45 Kimi K2 Thinking 55.4%
- 46 Claude Sonnet 4.5 thinking 55.3%
- 47
Nemotron 3 Super 55.2%
- 48 GPT-5 nano 54.9%
- 49
Qwen3.5-9B 54.5%
- 50 Kimi K2 Jul 2025 54.1%
- 51
Gemini 2.5 Pro Jun 2025 53.6%
- 52
MAI-Thinking-1 53%
- 53 GLM-4.5 52.8%
- 54 Claude 3.7 Sonnet thinking 51.6%
- 55 GPT-5.1 Instant 51.2%
- 56
Ring-1T 50.9%
- 57 Claude Haiku 4.5 thinking 50.5%
- 58
Qwen3.5-4B 49%
- 59
DeepSeek-V3.1 46.1%
- 60 gpt-oss-120b 45.3%
- 61
Nemotron-Cascade 2 30B-A3B 45.3%
- 62 o4-mini high 44.9%
- 63
MiniMax-M1-80k 44.7%
- 64
Gemma 4 E4B thinking 43.2%
- 65 GLM-4.5-Air 42.5%
- 66
Qwen3-235B-A22B 41.2%
- 67 GPT-4.1 39.4%
- 68
Nemotron 3 Nano 4B thinking 38.7%
- 69
Nemotron 3 Nano 30B-A3B 38.5%
- 70
Gemini 2.0 Flash Feb 2025 36.4%
- 71
Gemma 4 E2B thinking 36%
- 72 GPT-4.1 mini 35.8%
- 73
Qwen3.5-2B 33.7%
- 74
Llama 3.1-8B 23.7%
- 75
Gemma 3 4B 22.8%
- 76
Qwen3.5-0.8B 18.9%
- 77 GPT-4.1 nano 15%
Sources: Official MultiChallenge leaderboard and labs’ model cards
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6.1 Sol | 82% | Sep 2026 | Official leaderboard | |
| 2 | | 78.7% | Sep 2026 | Official leaderboard | |
| 3 | | 75.5% | Apr 2026 | Official leaderboard | |
| 4 | | 75.3% | Jul 2026 | Official leaderboard | |
| 5 | | 74.9% | Oct 2026 | Official leaderboard | |
| 6 | | 74.2% | Oct 2026 | Official leaderboard | |
| 7 | GPT-6.1 Terra | 74.2% | Oct 2026 | Official leaderboard | |
| 8 | | 71.4% | Feb 2026 | Official leaderboard | |
| 9 | GPT-5.4 Pro | 69.2% | Mar 2026 | Official leaderboard | |
| 10 | Claude Haiku 5.5 | 67.7% | Oct 2026 | Official leaderboard | |
| 11 | | 65.7% | Nov 2025 | Official leaderboard | |
| 12 | GPT-5.1 | 63.4% | thinking | Nov 2025 | Official leaderboard |
| 13 | GPT-5 | 63.2% | thinking | Aug 2025 | Official leaderboard |
| 14 | o3-pro | 62.4% | high | Jun 2025 | Official leaderboard |
| 15 | Kimi K2.5 | 61.4% | Jan 2026 | Official leaderboard | |
| 16 | | 60.6% | Mar 2026 | Official leaderboard | |
| 17 | GPT-5 mini | 59% | thinking | Aug 2025 | Official leaderboard |
| 18 | Claude Opus 4.5 | 59% | thinking | Nov 2025 | Official leaderboard |
| 19 | Claude Opus 4 | 58.6% | thinking | May 2025 | Official leaderboard |
| 20 | Claude Opus 4.1 | 57.2% | thinking | Aug 2025 | Official leaderboard |
| 21 | Claude Sonnet 4 | 57.1% | thinking | May 2025 | Official leaderboard |
| 22 | o3 | 56.6% | high | Apr 2025 | Official leaderboard |
| 23 | | 56% | thinking | Oct 2026 | Official leaderboard |
| 24 | Claude Opus 4.6 | 56% | non-thinking | Feb 2026 | Official leaderboard |
| 25 | Kimi K2 Thinking | 55.4% | Nov 2025 | Official leaderboard | |
| 26 | Claude Sonnet 4.5 | 55.3% | thinking | Sep 2025 | Official leaderboard |
| 27 | | 53.6% | Jun 2025 | Official leaderboard | |
| 28 | Claude 3.7 Sonnet | 51.6% | thinking | Feb 2025 | Official leaderboard |
| 29 | GPT-5.1 Instant | 51.2% | Nov 2025 | Official leaderboard | |
| 30 | Claude Haiku 4.5 | 50.5% | thinking | Oct 2025 | Official leaderboard |
| 31 | | 46.1% | Aug 2025 | Official leaderboard | |
| 32 | gpt-oss-120b | 45.3% | Aug 2025 | Official leaderboard | |
| 33 | o4-mini | 44.9% | high | Apr 2025 | Official leaderboard |
| 34 | | 43.2% | thinking | Mar 2026 | Official leaderboard |
| 35 | | 41.2% | Apr 2025 | Official leaderboard | |
| 36 | GPT-4.1 | 39.4% | Apr 2025 | Official leaderboard | |
| 37 | | 38.7% | thinking | Mar 2026 | Official leaderboard |
| 38 | | 36.4% | Feb 2025 | Official leaderboard | |
| 39 | | 36% | thinking | Mar 2026 | Official leaderboard |
| 40 | Ministral 3 8B | 27.8% | thinking | Official leaderboard | |
| 41 | Ministral 3 3B | 25.7% | thinking | Official leaderboard | |
| 42 | | 25.1% | thinking | Feb 2026 | Official leaderboard |
| 43 | | 23.7% | Jul 2024 | Official leaderboard | |
| 44 | | 22.8% | Mar 2025 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6.1 Sol | 82% | Sep 2026 | Official leaderboard | |
| 2 | | 78.7% | Sep 2026 | Official leaderboard | |
| 3 | | 77.7% | Dec 2025 | Lab model card | |
| 4 | | 76.6% | Dec 2025 | Lab model card | |
| 5 | | 75.5% | Apr 2026 | Official leaderboard | |
| 6 | | 75.5% | Dec 2025 | Lab model card | |
| 7 | | 75.3% | Jul 2026 | Official leaderboard | |
| 8 | | 74.9% | Oct 2026 | Official leaderboard | |
| 9 | | 74.2% | Oct 2026 | Official leaderboard | |
| 10 | GPT-6.1 Terra | 74.2% | Oct 2026 | Official leaderboard | |
| 11 | | 71.4% | Feb 2026 | Official leaderboard | |
| 12 | | 69.9% | Apr 2026 | Lab model card | |
| 13 | | 69.8% | Oct 2026 | Lab model card | |
| 14 | GPT-5 | 69.6% | Aug 2025 | Lab model card | |
| 15 | GPT-5.4 Pro | 69.2% | Mar 2026 | Official leaderboard | |
| 16 | | 68.3% | Feb 2026 | Lab model card | |
| 17 | Claude Haiku 5.5 | 67.7% | Oct 2026 | Official leaderboard | |
| 18 | | 67.6% | Feb 2026 | Lab model card | |
| 19 | | 66.7% | Dec 2025 | Lab model card | |
| 20 | | 66% | Feb 2026 | Lab model card | |
| 21 | | 65.7% | Nov 2025 | Official leaderboard | |
| 22 | GLM-5 | 64.8% | Feb 2026 | Lab model card | |
| 23 | | 63.8% | Jun 2026 | Lab model card | |
| 24 | GPT-5.1 | 63.4% | thinking | Nov 2025 | Official leaderboard |
| 25 | | 63.3% | Jan 2026 | Lab model card | |
| 26 | | 62.6% | Jan 2026 | Lab model card | |
| 27 | | 62.6% | Dec 2025 | Lab model card | |
| 28 | o3-pro | 62.4% | high | Jun 2025 | Official leaderboard |
| 29 | GPT-5 mini | 62.3% | Aug 2025 | Lab model card | |
| 30 | | 61.5% | Feb 2026 | Lab model card | |
| 31 | Kimi K2.5 | 61.4% | Jan 2026 | Official leaderboard | |
| 32 | | 61% | Jul 2026 | Lab model card | |
| 33 | | 60.8% | Feb 2026 | Lab model card | |
| 34 | | 60.6% | Mar 2026 | Official leaderboard | |
| 35 | Mercury 3 | 60.4% | Oct 2026 | Lab model card | |
| 36 | | 60% | Feb 2026 | Lab model card | |
| 37 | Claude Opus 4.5 | 59% | thinking | Nov 2025 | Official leaderboard |
| 38 | Claude Opus 4 | 58.6% | thinking | May 2025 | Official leaderboard |
| 39 | Claude Opus 4.1 | 57.2% | thinking | Aug 2025 | Official leaderboard |
| 40 | Claude Sonnet 4 | 57.1% | thinking | May 2025 | Official leaderboard |
| 41 | o3 | 56.6% | high | Apr 2025 | Official leaderboard |
| 42 | | 56% | thinking | Oct 2026 | Official leaderboard |
| 43 | Claude Opus 4.6 | 56% | non-thinking | Feb 2026 | Official leaderboard |
| 44 | | 55.7% | Feb 2026 | Lab model card | |
| 45 | Kimi K2 Thinking | 55.4% | Nov 2025 | Official leaderboard | |
| 46 | Claude Sonnet 4.5 | 55.3% | thinking | Sep 2025 | Official leaderboard |
| 47 | | 55.2% | Mar 2026 | Lab model card | |
| 48 | GPT-5 nano | 54.9% | Aug 2025 | Lab model card | |
| 49 | | 54.5% | Mar 2026 | Lab model card | |
| 50 | Kimi K2 Jul 2025 | 54.1% | Jul 2025 | Lab model card | |
| 51 | | 53.6% | Jun 2025 | Official leaderboard | |
| 52 | | 53% | Jun 2026 | Lab model card | |
| 53 | GLM-4.5 | 52.8% | Aug 2025 | Lab model card | |
| 54 | Claude 3.7 Sonnet | 51.6% | thinking | Feb 2025 | Official leaderboard |
| 55 | GPT-5.1 Instant | 51.2% | Nov 2025 | Official leaderboard | |
| 56 | | 50.9% | Oct 2025 | Lab model card | |
| 57 | Claude Haiku 4.5 | 50.5% | thinking | Oct 2025 | Official leaderboard |
| 58 | | 49% | Mar 2026 | Lab model card | |
| 59 | | 46.1% | Aug 2025 | Official leaderboard | |
| 60 | gpt-oss-120b | 45.3% | Aug 2025 | Official leaderboard | |
| 61 | | 45.3% | Mar 2026 | Lab model card | |
| 62 | o4-mini | 44.9% | high | Apr 2025 | Official leaderboard |
| 63 | | 44.7% | Jun 2025 | Lab model card | |
| 64 | | 43.2% | thinking | Mar 2026 | Official leaderboard |
| 65 | GLM-4.5-Air | 42.5% | Aug 2025 | Lab model card | |
| 66 | | 41.2% | Apr 2025 | Official leaderboard | |
| 67 | GPT-4.1 | 39.4% | Apr 2025 | Official leaderboard | |
| 68 | | 38.7% | thinking | Mar 2026 | Official leaderboard |
| 69 | | 38.5% | Dec 2025 | Lab model card | |
| 70 | | 36.4% | Feb 2025 | Official leaderboard | |
| 71 | | 36% | thinking | Mar 2026 | Official leaderboard |
| 72 | GPT-4.1 mini | 35.8% | Apr 2025 | Lab model card | |
| 73 | | 33.7% | Mar 2026 | Lab model card | |
| 74 | | 23.7% | Jul 2024 | Official leaderboard | |
| 75 | | 22.8% | Mar 2025 | Official leaderboard | |
| 76 | | 18.9% | Mar 2026 | Lab model card | |
| 77 | GPT-4.1 nano | 15% | Apr 2025 | Lab model card |
Labs report scores for 42 models in their cards. Switch the scores above to rank them together.
12 models have held number one on the official leaderboard since its release in January 2025 9 models have held number one with claims included since its release in January 2025
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
Sources: Official MultiChallenge leaderboard and labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official MultiChallenge leaderboard and labs’ model cards
5 labs 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.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Oct 23, 2026 | 55.6 | MultiChallenge | |
| Oct 19, 2026 | Mercury 3 | 60.4 | MultiChallenge |
| Oct 13, 2026 | 69.8 | MultiChallenge | |
| Jul 22, 2026 | 61 | Multi-Challenge | |
| Jun 4, 2026 | 63.8 | Multi-Challenge | |
| Jun 2, 2026 | 53 | Multi-Challenge | |
| Apr 28, 2026 | 69.9 | MultiChallenge | |
| Mar 19, 2026 | 45.3 | Scale AI Multi-Challenge | |
| Mar 11, 2026 | 55.2 | Scale AI Multi-Challenge | |
| Mar 2, 2026 | 18.9 | MultiChallenge | |
| Mar 2, 2026 | 33.7 | MultiChallenge | |
| Mar 2, 2026 | 49 | MultiChallenge | |
| Mar 2, 2026 | 54.5 | MultiChallenge | |
| Feb 24, 2026 | 60 | MultiChallenge | |
| Feb 24, 2026 | 60.8 | MultiChallenge | |
| Feb 24, 2026 | 61.5 | MultiChallenge | |
| Feb 16, 2026 | 67.6 | MultiChallenge | |
| Feb 14, 2026 | 68.3 | MultiChallenge | |
| Feb 6, 2026 | 66 | MultiChallenge | |
| Jan 23, 2026 | 63.3 | MultiChallenge | |
| Dec 18, 2025 | 66.7 | MultiChallenge | |
| Dec 15, 2025 | 38.5 | Scale AI Multi Challenge | |
| Dec 5, 2025 | 62.6 | Multi Challenge | |
| Dec 2, 2025 | 75.5 | MultiChallenge acc | |
| Dec 2, 2025 | 76.6 | MultiChallenge acc | |
| Dec 2, 2025 | 77.7 | MultiChallenge acc | |
| Aug 7, 2025 | GPT-5 nano | 54.9 | Scale MultiChallenge (o3-mini grader) |
| Aug 7, 2025 | GPT-5 mini | 62.3 | Scale MultiChallenge (o3-mini grader) |
| Aug 7, 2025 | GPT-5 | 69.6 | Scale MultiChallenge** Multi-turn instruction following |
| Jul 11, 2025 | Kimi K2 | 54.1 | Multi-Challenge, Acc |
| Jun 16, 2025 | 44.7 | MultiChallenge | |
| Apr 16, 2025 | o4-mini | 43 | Scale MultiChallenge |
| Apr 16, 2025 | o3 | 56.5 | Scale MultiChallenge Multi-turn instruction following |
| Apr 14, 2025 | GPT-4.1 nano | 15 | MultiChallenge (GPT-4o grader) 15.0 (o3-mini grader 31.1) |
| Apr 14, 2025 | GPT-4.1 mini | 35.8 | MultiChallenge (GPT-4o grader) 35.8 (o3-mini grader 42.2) |
| Apr 14, 2025 | GPT-4.1 | 38.3 | MultiChallenge |
21 system cards report it, from 11 labs
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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Oct 23, 2026 | | 55.6 | MultiChallenge, released Q4_K_M imatrix checkpoint (Table 5). BF16 53.1 (Table 3) | Capabilities |
| Jul 22, 2026 | | 61 | Multi-Challenge (Table 3) | Capabilities |
| Jun 9, 2026 | | 63.8 | Multi-Challenge (Table 10) | Capabilities |
| Jun 2, 2026 | | 53 | Multi-Challenge, Gemini 2.5 Pro judge (Table 12, rounded) | Capabilities |
| Mar 21, 2026 | | 66.7 | MultiChallenge (Table 1) | Capabilities |
| Mar 19, 2026 | | 45.3 | Scale AI Multi-Challenge (Table 1) | Capabilities |
| Mar 11, 2026 | | 55.2 | Scale AI Multi-Challenge (Table 5) | Capabilities |
| Feb 17, 2026 | GLM-5 technical report | 64.8 | Multi Challenge, Instruction Following panel (Figure 11) | Capabilities |
| Feb 14, 2026 | | 68.3 | MultiChallenge (Table 3) | Capabilities |
| Feb 11, 2026 | | 55.7 | MultiChallenge, o3-mini judge (Table 5). PaCoRe 60.8 | Capabilities |
| Feb 4, 2026 | | 66 | MultiChallenge (Table 2) | Capabilities |
| Jan 14, 2026 | | 62.6 | MultiChallenge, SeRe (Table 2) | Capabilities |
| Dec 23, 2025 | | 38.5 | Scale AI Multi Challenge (Table 3) | Capabilities |
| Dec 2, 2025 | | 75.5 | MultiChallenge acc (Table 5) | Capabilities |
| Dec 2, 2025 | | 76.6 | MultiChallenge acc (Table 1) | Capabilities |
| Dec 2, 2025 | | 77.7 | MultiChallenge acc (Table 1) | Capabilities |
| Oct 21, 2025 | | 50.9 | MultiChallenge (Table 1) | Capabilities |
| Aug 8, 2025 | GLM-4.5 technical report | 52.8 | MultiChallenge (Table 6) | Capabilities |
| Aug 8, 2025 | GLM-4.5-Air technical report | 42.5 | MultiChallenge (Table 6) | Capabilities |
| Jul 21, 2025 | Kimi K2 technical report | 54.1 | Multi-Challenge (Acc.) (Table 3) | Capabilities |
| Jun 16, 2025 | | 44.7 | MultiChallenge, GPT-4o judge (Table 2) | Capabilities |
The lab's number comes out ahead in 3 of 6 pairs that differ
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 |
|---|---|---|---|
| | 49% MultiChallenge | 25.1% Leaderboard, thinking | +24 pts |
| GPT-5 | 69.6% Scale MultiChallenge** Multi-turn instruction following | 63.2% Leaderboard, thinking | +6.4 pts |
| GPT-5 mini | 62.3% Scale MultiChallenge (o3-mini grader) | 59% Leaderboard, thinking | +3.3 pts |
| o4-mini | 43% Scale MultiChallenge | 44.9% Leaderboard, high | −1.9 pts |
| GPT-4.1 | 38.3% MultiChallenge | 39.4% Leaderboard | −1.1 pts |
| | 55.6% MultiChallenge | 56% Leaderboard, thinking | −0.4 pts |
| o3 | 56.5% Scale MultiChallenge Multi-turn instruction following | 56.6% Leaderboard, high | Same |
More in Instructions and chat
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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%
- 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%
- HANDBOOK.md In use Agents do routine company work with mock email, chat, calendar, issue and commerce tools while following a 20 to 124 page handbook. Programmatic criteria check required and forbidden actions, and a trial passes only if all pass. Claude Opus 5.5 52.3%