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BenchLM
Data

Claude Opus 4.8 vs Hy4 preview

Updated October 13, 2026. Rank says Claude Opus 4.8 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 Opus 4.8 has the higher public point estimate, 69.04 versus 60.86. Their conditional score ranges overlap. These ranges do not establish rank confidence. 11 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

69.04/100

Supported · Public rank #19

90% interval 65.1–73.0

Model B
Tencent logo

Tencent

60.86/100

Estimated · Public rank #48

Conditional range 46.5–75.2

Shared results
11
Claude Opus 4.8 only
29
Hy4 preview only
19
Like-for-like categories
1 / 8
Supported: Claude Opus 4.8 · Estimated: Hy4 preview. 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Claude Opus 4.8

    Claude Opus 4.8 has the higher public coding point estimate, 60.9 to 57.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
Show secondary and unsupported calls
  • Agentic work

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

    Not enough matched evidence

    Hy4 preview is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited
  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented
  • 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

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

    Confidence: rate-fallback
  • 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.

60.9Claude Opus 4.857.1Hy4 preview

Like-for-like · BenchAlign v5.8

Claude Opus 4.8 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.

Coding

Like-for-like
Claude Opus 4.8
60.9
Supported · #19/148
Hy4 preview
57.1
Supported · #26/148
Basis
BenchAlign v5.8 lane · 11 vs 8 public rows
Reading
Claude Opus 4.8 leads · intervals overlap

Agentic

Directional only
Claude Opus 4.8
62.3
Supported · #18/123
Hy4 preview
54.5
Estimated · #37/123
Basis
BenchAlign v5.8 lane · 12 vs 15 public rows
Reading
Directional only

Knowledge

Directional only
Claude Opus 4.8
71.1
Supported · #15/180
Hy4 preview
63.6
Estimated · #39/180
Basis
BenchAlign v5.8 lane · 6 vs 4 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 4.8
62.8
#25/29
Hy4 preview
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.8
91.2
#5/54
Hy4 preview
88.3
Unranked · 1 rankable row
Basis
Provisional lane · 2 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.8
Not ranked
Hy4 preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.8
75.4
#61/127
Hy4 preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.8
84.4
#1/12
Hy4 preview
Not ranked
Basis
Provisional lane · 3 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 Opus 4.8
$0.0175
Fits in one request
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request

Hy4 preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.8
$0.325
Fits in one request
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request

Hy4 preview has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 4.8
$1.35
Fits in one request
Cached input priced at the published list-input rate
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Hy4 preview 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 Opus 4.8

Not published

Hy4 preview

No comparable hosted API rate

Tencent Hy4 preview model card

Reasoning profile

Claude Opus 4.8

Reasoning

Hy4 preview

Reasoning

Weight access

Claude Opus 4.8

Proprietary

Hy4 preview

Open Weight

License

Claude Opus 4.8

Proprietary

Hy4 preview

Open Weight

Release date

Claude Opus 4.8

2026-05-28

Hy4 preview

2026-08-28

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 Opus 4.8 has the higher public point estimate, 69.04 versus 60.86. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Opus 4.8 or Hy4 preview?

Claude Opus 4.8 has the higher public point estimate, 69.04 versus 60.86. Their conditional score ranges 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 Opus 4.8 or Hy4 preview?

Claude Opus 4.8 has the higher public coding point estimate, 60.9 to 57.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Claude Opus 4.8 or Hy4 preview?

Claude Opus 4.8 scores higher for agentic tasks on the public lane, 62.3 to 54.5. Hy4 preview 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 Opus 4.8 or Hy4 preview?

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 Opus 4.8 or Hy4 preview?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence59 rows

Agentic

  • Terminal-Bench 3.0

    Claude Opus 4.821.1%
    Source
    Hy4 preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 4.874.6%
    Source
    Hy4 preview85.4%
    Source

    Hy4 preview leads this result

  • BrowseComp

    Claude Opus 4.884.3%
    Source
    Hy4 preview—

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.893.1%
    Source
    Hy4 preview—

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.883.4%
    Source
    Hy4 preview—

    Not directly comparable

  • Finance Agent v2

    Claude Opus 4.853.9%
    Source
    Hy4 preview—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.882.2%
    Source
    Hy4 preview83.7%
    Source

    Hy4 preview leads this result

  • Toolathlon

    Claude Opus 4.859.9%
    Source
    Hy4 preview—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.872.97%
    Source
    Hy4 preview—

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.821.1%
    Source
    Hy4 preview—

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 4.820.6%
    Source
    Hy4 preview—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Opus 4.871.9%
    Source
    Hy4 preview55.1%
    Source

    Claude Opus 4.8 leads this result

  • CyberGym

    Claude Opus 4.8—
    Hy4 preview78.4%
    Source

    Not directly comparable

  • WideResearch

    Claude Opus 4.8—
    Hy4 preview83.9%
    Source

    Not directly comparable

  • DRACO

    Claude Opus 4.8—
    Hy4 preview77.2%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 4.8—
    Hy4 preview74.1%
    Source

    Not directly comparable

  • APEX-Agents

    Claude Opus 4.8—
    Hy4 preview37.1%
    Source

    Not directly comparable

  • skillsBench

    Claude Opus 4.8—
    Hy4 preview62.9%
    Source

    Not directly comparable

  • JobBench

    Claude Opus 4.8—
    Hy4 preview61.7%
    Source

    Not directly comparable

  • Agents' Last Exam

    Claude Opus 4.8—
    Hy4 preview22.8%
    Source

    Not directly comparable

  • AutomationBench

    Claude Opus 4.8—
    Hy4 preview32.1%
    Source

    Not directly comparable

  • BankerToolBench

    Claude Opus 4.8—
    Hy4 preview78.6%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude Opus 4.8—
    Hy4 preview55.4%
    Source

    Not directly comparable

  • CWE-bench v1

    Claude Opus 4.8—
    Hy4 preview53.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.888.6%
    Source
    Hy4 preview—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.869.2%
    Source
    Hy4 preview65.7%
    Source

    Claude Opus 4.8 leads this result

  • SWE Multilingual

    Claude Opus 4.884.4%
    Source
    Hy4 preview82.9%
    Source

    Claude Opus 4.8 leads this result

  • SWE Multimodal

    Claude Opus 4.838.4%
    Source
    Hy4 preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 4.874.6%
    Source
    Hy4 preview85.4%
    Source

    Hy4 preview leads this result

  • cursorBench31

    Claude Opus 4.858.4%
    Source
    Hy4 preview—

    Not directly comparable

  • CursorBench 3.2

    Claude Opus 4.862.3%
    Source
    Hy4 preview—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 4.846.5%
    Source
    Hy4 preview—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Opus 4.887.8%
    Source
    Hy4 preview—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Opus 4.888.6%
    Source
    Hy4 preview—

    Not directly comparable

  • PostTrainBench v1.1

    Claude Opus 4.832.9%
    Source
    Hy4 preview—

    Not directly comparable

  • DeepSWE

    Claude Opus 4.8—
    Hy4 preview64.3%
    Source

    Not directly comparable

  • NL2Repo

    Claude Opus 4.8—
    Hy4 preview58.9%
    Source

    Not directly comparable

  • ProgramBench

    Claude Opus 4.8—
    Hy4 preview17.5%
    Source

    Not directly comparable

  • PostTrain Bench

    Claude Opus 4.8—
    Hy4 preview35.6%
    Source

    Not directly comparable

  • sweMarathon

    Claude Opus 4.8—
    Hy4 preview31.9%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Opus 4.872.1%
    Source
    Hy4 preview—

    Not directly comparable

  • ARC-AGI-3

    Claude Opus 4.81.5%
    Source
    Hy4 preview—

    Not directly comparable

  • ARC-AGI-1

    Claude Opus 4.892.50%
    Source
    Hy4 preview—

    Not directly comparable

  • CritPt

    Claude Opus 4.8—
    Hy4 preview16.9%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Claude Opus 4.866.2%
    Source
    Hy4 preview66.2%
    Source

    Tie

  • ScreenSpot Pro

    Claude Opus 4.887.9%
    Source
    Hy4 preview—

    Not directly comparable

  • CharXiv

    Claude Opus 4.889.9%
    Source
    Hy4 preview—

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.880.5%
    Source
    Hy4 preview—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.893.6%
    Source
    Hy4 preview92.3%
    Source

    Claude Opus 4.8 leads this result

  • GPQA-D

    Claude Opus 4.893.6%
    Source
    Hy4 preview92.3%
    Source

    Claude Opus 4.8 leads this result

  • HLE

    Claude Opus 4.857.9%
    Source
    Hy4 preview55.4%
    Source

    Claude Opus 4.8 leads this result

  • HLE w/o tools

    Claude Opus 4.849.8%
    Source
    Hy4 preview43.4%
    Source

    Claude Opus 4.8 leads this result

  • GPQA Diamond (Vals)

    Claude Opus 4.892.4%
    Source
    Hy4 preview—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Opus 4.889.6%
    Source
    Hy4 preview—

    Not directly comparable

Multilingual

  • INCLUDE

    Claude Opus 4.887.6%
    Source
    Hy4 preview—

    Not directly comparable

Math

  • USAMO 2026

    Claude Opus 4.896.7%
    Source
    Hy4 preview—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.880.000%
    Source
    Hy4 preview—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.856.098%
    Source
    Hy4 preview—

    Not directly comparable

  • Apex

    Claude Opus 4.8—
    Hy4 preview74.2%
    Source

    Not directly comparable

59 public results · 11 shared

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Last updated October 13, 2026