The first entry is always the pin's source. Overall confidence is a weighted average of how firmly each reference supports the start and end times used above; a reference counts half as much for every 180 days older than the newest.
IBM's Hugging Face[5] announcement 'Granite 4.2 LLMs: How They're Built' and the ibm-granite/granite-4.2-8b model card both give the release as August 25, 2026; OpenRouter[2] lists the 8B on 31 August, which is when the router added it.
Router listing of the 8B: 131,072-token context and $0.06 per 1 million input tokens and $0.25 per 1 million output tokens.[1]
Independent trade report: Granite 4.1 (April) stressed answering without long reasoning chains, 4.2 makes reasoning optional; only the 8B and 30B got the agentic RL stage; 1 trillion synthetic code tokens from CodeAlchemy; IBM's 30B resolves 57% on SWE-bench Verified.[1]
Releases are dated 25 August 2026; flags that the benchmark figures are IBM's own runs, that the models are text-only, and that Qwen3.8-27B leads on published coding benchmarks.[1]
IBM's model card for the 8B: dense decoder-only, post-trained from Granite-4.1-8B-Base, Apache 2.0, 12 tested languages, thinking / non-thinking / low-effort modes, GRPO then RLHF post-training on a GB200 NVL72 cluster at CoreWeave, and the 3B/8B/30B results table.[1]
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| Benchmark | Granite 4.2 3B | Granite 4.2 8B | Granite 4.2 30B |
|---|---|---|---|
| SWE-bench Verified (agentic coding) | n/a | 47.67 | 57.00 |
| SWE-bench Multilingual (agentic coding) | n/a | 30.78 | 41.89 |
| SWE-bench Pro (agentic coding) | n/a | 19.11 | 33.29 |
| Terminal-Bench 2.1 (agentic coding) | n/a | 20.56 | 29.24 |
| τ³-bench average (agentic, general) | 45.78 | 58.06 | 62.00 |
| AIME25 (reasoning) | 78.33 | 86.67 | 89.17 |
| HMMT Feb25 (reasoning) | 66.67 | 78.33 | 89.17 |
| GPQA (reasoning) | 54.80 | 64.14 | 66.41 |
| LiveCodeBench v6 (reasoning) | 69.71 | 73.24 | 75.77 |
| SciCode (reasoning) | 24.11 | 36.09 | 38.76 |
| MMLU-Pro (chat and instruction following) | 67.84 | 74.04 | 77.60 |
| Arena-Hard-V2 (chat and instruction following) | 34.96 | 65.19 | 67.93 |
| IFBench, prompt (chat and instruction following) | 74.33 | 79.33 | 77.17 |
| RULER 64K (long context) | 67.52 | 80.99 | 89.96 |
| RULER 128K (long context) | 55.30 | 71.41 | 81.38 |