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BenchLM
Data

Claude Sonnet 5 vs Granite 4.2 8B

Updated October 15, 2026. Rank says Claude Sonnet 5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Claude Sonnet 5 has the higher public point estimate, 64.83 versus 33.4. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Anthropic logo

Anthropic

64.83/100

Supported · Public rank #36

90% interval 59.9–69.8

Model B
IBM logo

IBM

33.4/100

Estimated · Public rank #166

Conditional range 23.7–43.1

Shared results
5
Claude Sonnet 5 only
24
Granite 4.2 8B only
9
Like-for-like categories
1 / 8
Supported: Claude Sonnet 5 · Estimated: Granite 4.2 8B. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Claude Sonnet 5

    Claude Sonnet 5 has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Granite 4.2 8B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Granite 4.2 8B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited
  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B has no comparable published API token rate.

    Confidence: listed-rates
  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

57.5Claude Sonnet 517.2Granite 4.2 8B

Directional only · BenchAlign v5.8

Claude Sonnet 5 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Knowledge

Like-for-like
Claude Sonnet 5
65.3
Supported · #34/184
Granite 4.2 8B
30.6
Supported · #154/184
Basis
BenchAlign v5.8 lane · 6 vs 2 public rows
Reading
Claude Sonnet 5 leads

Agentic

Directional only
Claude Sonnet 5
66.4
Supported · #15/127
Granite 4.2 8B
15.7
Estimated · #113/127
Basis
BenchAlign v5.8 lane · 8 vs 3 public rows
Reading
Directional only

Coding

Directional only
Claude Sonnet 5
57.5
Supported · #25/150
Granite 4.2 8B
17.2
Estimated · #125/150
Basis
BenchAlign v5.8 lane · 11 vs 6 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Sonnet 5
82.2
Unranked · 2 rankable rows
Granite 4.2 8B
56.8
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 5
82.0
#15/54
Granite 4.2 8B
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5
Not ranked
Granite 4.2 8B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5
Not ranked
Granite 4.2 8B
86.5
#41/146
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5
69.4
Unranked · 2 rankable rows
Granite 4.2 8B
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Sonnet 5
$0.007
Fits in one request
Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5
$0.13
Fits in one request
Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Sonnet 5
$0.18
Fits in one request
Granite 4.2 8B
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable

Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Sonnet 5

$0.2 per 1M cached input tokens

Claude API pricing

Granite 4.2 8B

No comparable hosted API rate

IBM Granite 4.2 8B model card

Reasoning profile

Claude Sonnet 5

Reasoning

Granite 4.2 8B

Reasoning

Weight access

Claude Sonnet 5

Proprietary

Granite 4.2 8B

Open Weight

License

Claude Sonnet 5

Proprietary

Granite 4.2 8B

Open Weight

Release date

Claude Sonnet 5

2026-06-30

Granite 4.2 8B

2026-08-25

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Claude Sonnet 5 has the higher public point estimate, 64.83 versus 33.4. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Sonnet 5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Sonnet 5 or Granite 4.2 8B?

Claude Sonnet 5 has the higher public point estimate, 64.83 versus 33.4. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Sonnet 5 or Granite 4.2 8B?

Claude Sonnet 5 scores higher for coding on the public lane, 57.5 to 17.2. Granite 4.2 8B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Sonnet 5 or Granite 4.2 8B?

Claude Sonnet 5 scores higher for agentic tasks on the public lane, 66.4 to 15.7. Granite 4.2 8B is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Sonnet 5 or Granite 4.2 8B?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Claude Sonnet 5 or Granite 4.2 8B?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 128K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence38 rows

Agentic

  • Terminal-Bench 3.0

    Claude Sonnet 514.6%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 580.4%
    Source
    Granite 4.2 8B20.6%
    Source

    Claude Sonnet 5 leads this result

  • BrowseComp

    Claude Sonnet 584.7%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 557.4%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • OSWorld-Verified

    Claude Sonnet 581.2%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Sonnet 574.5%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • ApprenticeBench

    Claude Sonnet 516%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • MazeBench

    Claude Sonnet 50%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • τ³-bench results

    Claude Sonnet 5—
    Granite 4.2 8B58.1%
    Source

    Not directly comparable

  • BFCL v4

    Claude Sonnet 5—
    Granite 4.2 8B52.4%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 585.2%
    Source
    Granite 4.2 8B47.7%
    Source

    Claude Sonnet 5 leads this result

  • SWE-bench Pro

    Claude Sonnet 563.2%
    Source
    Granite 4.2 8B19.1%
    Source

    Claude Sonnet 5 leads this result

  • SWE Multilingual

    Claude Sonnet 578.3%
    Source
    Granite 4.2 8B30.8%
    Source

    Claude Sonnet 5 leads this result

  • SWE Multimodal

    Claude Sonnet 528.1%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 580.4%
    Source
    Granite 4.2 8B20.6%
    Source

    Claude Sonnet 5 leads this result

  • FrontierCode 1.1 Main

    Claude Sonnet 542.7%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • CursorBench 3.2

    Claude Sonnet 561.5%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • VulcanBench CII v1

    Claude Sonnet 589.2%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Sonnet 582.4%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Sonnet 579.6%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • CursorBench 4.0

    Claude Sonnet 534.1%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • LiveCodeBench v6

    Claude Sonnet 5—
    Granite 4.2 8B73.2%
    Source

    Not directly comparable

  • SciCode

    Claude Sonnet 5—
    Granite 4.2 8B36.1%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    Claude Sonnet 588.3%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • CharXiv w/o tools

    Claude Sonnet 577%
    Source
    Granite 4.2 8B—

    Not directly comparable

Knowledge

  • HLE

    Claude Sonnet 557.4%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 543.2%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • HLE-Verified

    Claude Sonnet 531.0%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • LABBench2

    Claude Sonnet 580.1%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Sonnet 588.9%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Sonnet 587.5%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • GPQA

    Claude Sonnet 5—
    Granite 4.2 8B64.1%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude Sonnet 5—
    Granite 4.2 8B74.0%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Claude Sonnet 5—
    Granite 4.2 8B79.3%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Sonnet 565.614%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Sonnet 529.268%
    Source
    Granite 4.2 8B—

    Not directly comparable

  • AIME 2025

    Claude Sonnet 5—
    Granite 4.2 8B86.7%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Claude Sonnet 5—
    Granite 4.2 8B78.3%
    Source

    Not directly comparable

38 public results · 5 shared

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Last updated October 15, 2026