BenchLeader

Granite 4.2 3B

Granite 4.2 3B is an IBM open-weights reasoning model, released 25 Aug 2026. Its best configuration ranks #497 of 751 on the BenchLeader Index at 45.0 ±4.7, in the lower half. The ± is the point: 300 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in knowledge (55) and lowest in agents & tools (33). At $0.053 per million tokens blended it is among the cheapest fifth of ranked models. Output speed of 221 tokens per second puts it in the fastest quarter, with a first answer in 9.6 s. Last measured 2 Oct 2026.

Blended price
$0.053/M
$0.030 in · $0.120 out
Output speed
221 tok/s
measured by Artificial Analysis
First answer
9.57 s
Context
131k
Full answer
12 s
median, reasoning included
Cost per run
$0.0060
one full Intelligence Index run
Released
25 Aug 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index45
  2. Reasoning43
  3. Coding50
  4. Agents & tools33
  5. Knowledge55
  6. Human preference44
  7. Long context37
  8. Composite40

Versions

IBM has shipped 2 models under this name. Each is ranked on its own results; a newer version often has fewer results so far, which holds its index nearer the average until more arrive.

ModelReleasedIndexRank
Granite 4.2 3Bthis page25 Aug 202645.0#497
Granite 4.1 3B–39.4#656

How its index has moved

9 Sept 2026 to 3 Oct 2026
404652

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Metadata

Benchmarknot statedSourceTrend
AA Openness Indexnot in index72.2#21Artificial Analysis

Reasoning

Coding

Benchmarknot statedSourceTrend
LMArena Coding1380#210LMArena
SciCode (AA)not in index25.4%#200Artificial Analysis
Terminal-Bench 4.0 (AA)not in index0.0%#137Artificial Analysis
Terminal-Bench 2.1 (AA)not in index13.9%#180Artificial Analysis

Agents & tools

Benchmarknot statedSourceTrend
GDPval (AA)not in index0.0%#197Artificial Analysis
τ²-Bench Banking (AA)5.6%#172Artificial Analysis
AutomationBenchnot in index0.4%#51Artificial Analysis
GDP.pdfnot in index0.2%#51Artificial Analysis
AA-Briefcasenot in index95#47Artificial Analysis

Knowledge

Instruction following

Benchmarknot statedSourceTrend
LMArena Instruction Followingnot in index1285#251LMArena

Human preference

Benchmarknot statedSourceTrend
LMArena Text1290#259LMArena
LMArena Creative Writingnot in index1205#291LMArena
LMArena Multi-turnnot in index1287#252LMArena
LMArena Longer Queriesnot in index1300#257LMArena

Long context

Benchmarknot statedSourceTrend
AA-LCR24.3%#390Artificial Analysis

Composite

Benchmarknot statedSourceTrend
AA Intelligence Index9.1#386Artificial Analysis

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0000–10.9 s
Summarise a 30-page report12,000 / 600$0.0004–12.3 s
Code edit6,000 / 1,500$0.0004–16.4 s
Agentic coding session60,000 / 4,000$0.0023–27.7 s
Structured extraction2,000 / 200$0.0001–10.5 s

See also

Data as of 4 Oct 2026. Compare with another model.

Cite as: BenchLeader, “Granite 4.2 3B: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/granite-4-2-3b, data as of 4 Oct 2026.