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The LLM benchmark aggregator.

Granite 4.2 3B

IBM · 3B

Strongest in Knowledge work (#158 of 178), weakest in Agents (#252 of 268). Above par in 1 of 14 scopes. Among the models it meets almost everywhere, it finishes behind GPT-5.6 Terra and Claude Sonnet 5 and ahead of Gemma 3 27B It and Gemini 2.0 Flash.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Core abilities42.9#170/204
General intelligence39.8#176/204
Human preference46.6#226/342
Human preference46.6#226/342
Agents38.8#252/268
Knowledge work35.4#158/178
Tool use48.2—/81✱
Reasoning48.9—/178✱
Mathematics52.6—/140✱
Science43.8—/122✱
Expert reasoning44—/0✱
Coding47.3—/165✱
Agentic coding46.7—/157✱
Code generation42.6—/77✱

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Granite 4.2 3B, left for the other.

G9v3 3Bwon 7 · lost 2
Qwen3.6 27Bwon 7 · lost 2
Grok Build 0.1won 7 · lost 2
K2 Horizon 0.9Bwon 7 · lost 3
GPT-4o Miniwon 8 · lost 4
Command Awon 7 · lost 4
GPT-4.1 Nanowon 7 · lost 5
DeepSeek V3won 7 · lost 5
Grok 4.3won 7 · lost 5
GPT-5.4 Miniwon 7 · lost 5
Claude 3.5 Haikuwon 5 · lost 4
Gemini 2.0 Flashwon 5 · lost 4
Gemma 3 27B Itwon 5 · lost 4
Llama 4 Scout Instructwon 5 · lost 5
Gemini 3.5 Flash Litewon 6 · lost 6
Mistral Medium 3.5won 5 · lost 6
Mimo V2.5won 4 · lost 5
MiniMax M3won 6 · lost 8
Inklingwon 6 · lost 8
Qwen3.6 Pluswon 5 · lost 7
Nemotron 3 Ultrawon 4 · lost 7
Mistral Large 3won 4 · lost 7
Kimi K2.7 Codewon 3 · lost 6
Mistral Smallwon 3 · lost 6
Inkling Smallwon 3 · lost 6
GPT-5.4 Nanowon 4 · lost 8
GPT OSS 120Bwon 3 · lost 8
GPT-4.1won 3 · lost 8
Granite 4.2 30Bwon 3 · lost 9
Kimi K2.6won 3 · lost 9
Qwen3.7 Maxwon 3 · lost 9
Gemini 3.1 Prowon 3 · lost 9
Granite 4.2 8Bwon 3 · lost 10
G9v3 39A5Bwon 2 · lost 7
Qwen3.8 Flash Nextwon 2 · lost 7
GPT-5 Nanowon 2 · lost 7
Gemini 2.5 Flash Litewon 2 · lost 7
MiniMax M2.5won 2 · lost 7
Grok 4 Fastwon 2 · lost 7
MiniMax M2.7won 2 · lost 7
Qwen3 Maxwon 2 · lost 7
Grok 4.1 Fastwon 2 · lost 7
GPT-5.1won 2 · lost 7
GLM-5won 2 · lost 7
Nemotron 3 Superwon 2 · lost 8
Claude Opus 4won 2 · lost 8
K2 Horizon 7Bwon 2 · lost 9
Kimi K2won 2 · lost 9
DeepSeek R1won 2 · lost 9
Gemini 3.1 Flash Litewon 2 · lost 9
Kimi K2.5won 2 · lost 9
Mimo V2.5 Prowon 2 · lost 9
GPT-4.1 Miniwon 2 · lost 10
GPT-5 Miniwon 2 · lost 10
Gemini 2.5 Flashwon 2 · lost 10
Claude Haiku 4.5won 2 · lost 10
GLM-4.6won 2 · lost 10
Claude Sonnet 4.5won 2 · lost 10
Grok 4.5won 2 · lost 10
GLM-5.3 Flashwon 2 · lost 10
Claude Opus 4.5won 2 · lost 10
Gemini 3.8 Flashwon 2 · lost 10
DeepSeek V4 Flashwon 2 · lost 11
Qwen3.8 27Bwon 2 · lost 12
Qwen3.5 4Bwon 1 · lost 8
Qwen3.5 9Bwon 1 · lost 9
O3 Miniwon 1 · lost 9
Qwen3.6 35B A3Bwon 1 · lost 10
Qwen3 235B A22B Instructwon 1 · lost 10
Grok 4.7won 1 · lost 10
GPT-6 Lunawon 1 · lost 10
Gemini 3 Prowon 1 · lost 10
Muse Spark 1.2won 1 · lost 10
O4 Miniwon 1 · lost 11
Claude Sonnet 4won 1 · lost 11
Gemini 2.5 Prowon 1 · lost 11
Claude Sonnet 4.6won 1 · lost 11
Gemini 3.5 Flashwon 1 · lost 11
Qwen3.8 Maxwon 1 · lost 11
Gemini 3.6 Flashwon 1 · lost 11
Muse Spark 1.1won 1 · lost 11
Gemma 4 31Bwon 1 · lost 12
GLM-5.3won 1 · lost 12
Kimi K3won 1 · lost 12
GPT-5.6 Lunawon 1 · lost 13
GLM-5.2won 1 · lost 13
Gemma 4 12Bwon 0 · lost 9
K2 Horizon 32Bwon 0 · lost 9
Muse Glimmer-30Bwon 0 · lost 9
GPT OSS 20Bwon 0 · lost 9
Qwen3 32Bwon 0 · lost 9
Grok 3 Miniwon 0 · lost 9
GLM-4.7won 0 · lost 9
GLM-5.1won 0 · lost 9
Muse Sparkwon 0 · lost 9
Mimo V2.6 Prowon 0 · lost 10
Claude Opus 4.6won 0 · lost 10
K2 Horizon MoVA 36B A4Bwon 0 · lost 11
K2 Horizon 375B A23Bwon 0 · lost 11
Grok 4won 0 · lost 11
GPT-5won 0 · lost 11
GPT-6 Solwon 0 · lost 11
GPT-6 Astrawon 0 · lost 11
Muse Spark 1.3won 0 · lost 11
Claude Opus 5.5won 0 · lost 11
K2 Horizon 3.7Bwon 0 · lost 12
DeepSeek V3.2won 0 · lost 12
O3won 0 · lost 12
GPT-5.2won 0 · lost 12
Grok 4.6won 0 · lost 12
GPT-5.4won 0 · lost 12
Claude Opus 4.8won 0 · lost 12
GPT-5.5won 0 · lost 12
Gemini 3.7 Flashwon 0 · lost 12
Claude Fable 5.1won 0 · lost 12
Claude Opus 4.7won 0 · lost 12
Claude Fable 5won 0 · lost 12
DeepSeek V4 Prowon 0 · lost 13
DeepSeek V4.1 Flashwon 0 · lost 13
GPT-5.6 Solwon 0 · lost 13
Claude Opus 5won 0 · lost 13
Claude Sonnet 5won 0 · lost 14
GPT-5.6 Terrawon 0 · lost 14

§ 3 · Sources

Where the numbers come from

5 publications, 12 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-09-26
LMArena Text 1292
Artificial Analysis ↗1 measureread 2026-09-26
Artificial Analysis Intelligence Index 9
GDPval-AA ↗1 measureread 2026-09-26
GDPval-AA 188
AA-Briefcase ↗1 measureread 2026-09-26
AA-Briefcase 99
tau3-Banking 5.6%Terminal-Bench 2.1 13.9%SciCode 24.9%GPQA Diamond 55.9%SWE-bench Verified 32.2%HMMT Feb 2026 57.2%HLE 6.6%BFCL v4 50.8%

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PublicAI Index badge for Granite 4.2 3B[![PublicAI Index](https://publicai.io/model-index/badge?model=granite-4-2-3b)](https://publicai.io/model-index/m/granite-4-2-3b)

✱ Placed by a one-off publication, not a board that re-ran the model. ✱✱ marks a figure the model’s own publisher printed, which counts for less again. Scores are 0–100 on the PublicAI Index scale, 50 = the average of the models each source lists. Scores belong to their publishers.

Snapshot 2026-09-26 · the full index · JSON API