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ibm · Open weights

Granite 4.2 8B

Added Aug 31, 2026Open weights

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Use in the app

IBM Granite 4.2 8B is an Apache 2.0-licensed dense model with native step-by-step reasoning and specialized training for agentic work. It can plan before acting, sequence tools, navigate codebases, work in terminals, and verify results across coding, search, mathematics, science, and complex instruction-following tasks.

  • Reasoning
  • Tools
  • Structured output
Input
Text
Output
Text
Reasoning effort
none · low · high
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.10
Output
$0.15
Cache read
$0.05

Reference prices as published by the model provider. API example

Specifications

Context window
131.1K
Max output
—
Average output (7 days)
2.4K tokens
Longer than 94% of 468 models

Side by side

Granite 4.2 8B compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Granite 4.2 8BibmThis modelGLM 4.5 AirZ.aiRemove
ProvideribmZ.ai
Discovery tierOpen weightsOpen weights
AddedAug 31, 2026Apr 15, 2025
Limits
Context window131.07KBest128K
Max output—98.3K
Average output2.4K tokens59 tokens
Pricing, USD per 1M tokens
Input$0.10Best$0.13
Output$0.15Best$0.85
Cache read$0.05$0.025Best
Performance
Throughput—90.9 tok/s
Time to first token—1.5 s
Request success (24h)100.0%100.0%
Benchmark indexes
Intelligence Index11.111.1
Coding Index22.4—
Math Index—80.7
Capabilities
ReasoningYesNo
ToolsYesYes
Structured outputYesYes
Reasoning effortnone, low, high—

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Granite 4.2 8B
  • GLM 4.5 Air

Intelligence Index

  • Granite 4.2 8B11.1
  • GLM 4.5 Air11.1

Granite 4.2 8B: Better than 23% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Granite 4.2 8B: 22.4
    • GLM 4.5 Air: —

  • Math Index

    Composite of the math evaluations

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 80.7

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Granite 4.2 8B: 2.1%
    • GLM 4.5 Air: —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Granite 4.2 8B: 0.3%
    • GLM 4.5 Air: —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Granite 4.2 8B: 310 Elo
    • GLM 4.5 Air: —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Granite 4.2 8B: 491 Elo
    • GLM 4.5 Air: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Granite 4.2 8B: 0.6%
    • GLM 4.5 Air: —

  • AA-LCRv1.1

    Reasoning across long documents

    • Granite 4.2 8B: 45.0%
    • GLM 4.5 Air: 46.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Granite 4.2 8B: 9.7%Top
    • GLM 4.5 Air: 7.0%

  • GPQA Diamond

    Graduate-level science questions

    • Granite 4.2 8B: 63.1%
    • GLM 4.5 Air: 73.3%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 81.5%

  • IFBench

    Following precise output instructions

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 37.6%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Granite 4.2 8B: 0.0%
    • GLM 4.5 Air: —

  • SciCode

    Scientific computing in Python

    • Granite 4.2 8B: 31.5%
    • GLM 4.5 Air: —

  • LiveCodeBench

    Recent competitive programming problems

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 68.4%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 80.7%

  • AIME

    Competition mathematics

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 67.3%

  • MATH-500

    Competition math problems

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 96.5%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 20.5%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Granite 4.2 8B: —
    • GLM 4.5 Air: 46.5%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Granite 4.2 8B: 45.0%
    • GLM 4.5 Air: 46.7%Top

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Request success (24h)
100.0%
Reliable
Hourly request success · last 72 hoursLowest hour 100.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "ibm-granite/granite-4.2-8b",
    "reasoning_effort": "none",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="ibm-granite/granite-4.2-8b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)