vs
0:2
overall capability wins (1 ties across 3 scored). Granite 4.2 30B leads overall.
- Specs0:2
Verdict
Granite 4.2 30B offers larger context (131K vs 128K).
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Granite 3.1 8B Instruct
- $0.08
- Granite 4.2 30B
- -
Price per 1M tokens
Full comparison
Organization
IBM
IBM
Family
Granite
Granite
License
Apache 2.0
Apache 2.0
Open weights
Yes
Yes
Release
Dec 18, 2024
Aug 25, 2026
Knowledge cutoff
-
-
API / provider
IBM watsonx
No primary API price listed
Modalities
text → text
text → text
Specs
Context window
128K
131K
Max output
8K
8K
Parameters
8B
30B
Pricing
Input $/1M
$0.05
—
Output $/1M
$0.10
—
Blended $/1M (3∶1)
$0.06
-
Speed
tok/s
110
-
TTFT (s)
0.15
-
Reasoning
MMLU-Pro
—
77.6
GPQA Diamond
—
64.4
Humanity's Last Exam
—
11.2
AIME 2025
—
89.2
MATH-500
—
—
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
—
10.1
AA-LCR v1.1
—
49.0
CritPt
—
0.3
MMMU-Pro
—
—
IFBench
—
—
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
57.0
SWE-bench Pro
—
33.3
SWE-bench Multilingual
—
41.9
LiveCodeBench
—
75.8
Terminal-Bench 2.1
—
26.6
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
—
37.8
CursorBench
—
—
SWE-Rebench
—
—
NL2Repo-Bench
—
—
DeepSWE
—
—
WebDev Arena
—
—
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
1,208
—
| Metric | Granite 3.1 8B Instruct | Granite 4.2 30B | Delta |
|---|---|---|---|
| Identity | |||
| Organization | IBM | IBM | — |
| Family | Granite | Granite | — |
| License | Apache 2.0 | Apache 2.0 | — |
| Open weights | Yes | Yes | — |
| Release | Dec 18, 2024 | Aug 25, 2026 | — |
| Knowledge cutoff | - | - | — |
| API / provider | IBM watsonx | No primary API price listed | — |
| Modalities | text → text | text → text | — |
| Specs | |||
| Context window | 128K | 131K | B +3K |
| Max output | 8K | 8K | tie |
| Parameters | 8B | 30B | B +22 |
| Pricing | |||
| Input $/1M | $0.05 | — | — |
| Output $/1M | $0.10 | — | — |
| Blended $/1M (3∶1) | $0.06 | - | — |
| Speed | |||
| tok/s | 110 | - | — |
| TTFT (s) | 0.15 | - | — |
| Reasoning | |||
| MMLU-Pro | — | 77.6 | — |
| GPQA Diamond | — | 64.4 | — |
| Humanity's Last Exam | — | 11.2 | — |
| AIME 2025 | — | 89.2 | — |
| MATH-500 | — | — | — |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | — | 10.1 | — |
| AA-LCR v1.1 | — | 49.0 | — |
| CritPt | — | 0.3 | — |
| MMMU-Pro | — | — | — |
| IFBench | — | — | — |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | 57.0 | — |
| SWE-bench Pro | — | 33.3 | — |
| SWE-bench Multilingual | — | 41.9 | — |
| LiveCodeBench | — | 75.8 | — |
| Terminal-Bench 2.1 | — | 26.6 | — |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | — | 37.8 | — |
| CursorBench | — | — | — |
| SWE-Rebench | — | — | — |
| NL2Repo-Bench | — | — | — |
| DeepSWE | — | — | — |
| WebDev Arena | — | — | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | 1,208 | — | — |
Granite 3.1 8B Instruct
- Context
- 128K / 8K out
- Parameters
- 8B
- Price
- $0.05 / $0.10
- Speed
- 110 tok/s · 0.15s TTFT
- Modalities
- text → text
- License
- Apache 2.0
Prior-gen IBM Granite 3.1 8B instruct — enterprise RAG and tool-calling baseline on watsonx before Granite 4.
Granite 4.2 30B
- Context
- 131K / 8K out
- Parameters
- 30B
- Price
- —
- Speed
- —
- Modalities
- text → text
- License
- Apache 2.0
IBM's Aug 25, 2026 flagship dense reasoning model (Apache 2.0) — native 128K context with a 512K long-context extension, switchable thinking / non-thinking / low-effort modes, and agentic RL on software-engineering, terminal, and search tasks. IBM reports SWE-bench Verified 57.00 and Terminal-Bench 2.1 29.24 under its NeMo Evaluator setup.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.
These two models have no overlapping published benchmarks in our dataset. Compare specs and pricing instead.