Agentic
Directional only- Claude Opus 4.8
- 80.3
- GLM-5.1
- 65.4
- Weighted basis
- 3 vs 2 rows
- Reading
- Directional only
Claude Opus 4.8 vs GLM-5.1
Updated August 26, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Opus 4.8 has the higher public score estimate, 76.45 versus 66.99, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
10 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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 Opus 4.8
Claude Opus 4.8 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
GLM-5.1
GLM-5.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
GLM-5.1
GLM-5.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
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. GLM-5.1 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GLM-5.1 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
23 Claude Opus 4.8 only
10 Shared
11 GLM-5.1 only
- Shared results
- 10
- Claude Opus 4.8 only
- 23
- GLM-5.1 only
- 11
- Like-for-like categories
- 0 / 8
4 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Directional only- Claude Opus 4.8
- 81.1
- GLM-5.1
- 61.3
- Weighted basis
- 2 vs 2 rows
- Reading
- Directional only
Knowledge
Directional only- Claude Opus 4.8
- 62.7
- GLM-5.1
- 52.3
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Math
Directional only- Claude Opus 4.8
- 53.9
- GLM-5.1
- 62.0
- Weighted basis
- 3 vs 4 rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Opus 4.8
- 72.1
- GLM-5.1
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not measured
- GLM-5.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 77.0
- GLM-5.1
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.8
- Not measured
- GLM-5.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | GLM-5.1 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 80.3 | 65.4 | Directional only3 vs 2 rows | Directional only |
| Coding | 81.1 | 61.3 | Directional only2 vs 2 rows | Directional only |
| Knowledge | 62.7 | 52.3 | Directional only2 vs 1 rows | Directional only |
| Math | 53.9 | 62.0 | Directional only3 vs 4 rows | Directional only |
| Reasoning | 72.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 77.0 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
FrontierMath v2 (Tier 4)
Math
BrowseComp
Agentic
FrontierMath v2 (Tiers 1-3)
Math
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
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
- GLM-5.1
- $0.0036
- Fits in one request
GLM-5.1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.8
- $0.325
- Fits in one request
- GLM-5.1
- $0.0832
- Fits in one request
GLM-5.1 has the lower modeled cost
Costs use the listed standard API rates.
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
- GLM-5.1
- $0.352
- Does not fit in one request
- Cached input priced at the published list-input rate
GLM-5.1 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GLM-5.1 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.8GLM-5.1
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
GLM-5.1
203K
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewGLM-5.1
Not sourced
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
GLM-5.1
Not published
Documented inputs
Claude Opus 4.8
text, image
Anthropic model overviewGLM-5.1
Not sourced
Documented outputs
Claude Opus 4.8
GLM-5.1
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewGLM-5.1
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
GLM-5.1
Reasoning
Weight access
Claude Opus 4.8
Proprietary
GLM-5.1
Open Weight
License
Claude Opus 4.8
Proprietary
GLM-5.1
Open Weight
Release date
Claude Opus 4.8
2026-05-28
GLM-5.1
2026-04-07
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 score estimate, 76.45 versus 66.99, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.325 vs $0.0832. Cache-heavy agent loop: $1.35 vs $0.352.
- Context tradeoff
- Claude Opus 4.8 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Claude Opus 4.8
API / mo$22,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
GLM-5.1
API / mo$4,350
Self-host / mo$18,221
Break-even264M/day
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence44 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceGLM-5.1—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceGLM-5.163.5%SourceClaude Opus 4.8 leads this result
BrowseComp
Claude Opus 4.884.3%SourceGLM-5.168%SourceClaude Opus 4.8 leads this result
DeepSearchQA
Claude Opus 4.893.1%SourceGLM-5.1—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceGLM-5.1—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceGLM-5.1—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceGLM-5.171.8%SourceClaude Opus 4.8 leads this result
Toolathlon
Claude Opus 4.859.9%SourceGLM-5.1—Not directly comparable
Gert Labs
Shared sourceClaude Opus 4.872.97%GLM-5.160.11%Claude Opus 4.8 leads this result
ResearchClawBench
Shared sourceClaude Opus 4.821.1%GLM-5.118.2%Claude Opus 4.8 leads this result
OSWorld 2.0
Claude Opus 4.820.6%SourceGLM-5.1—Not directly comparable
τ³-bench results
Claude Opus 4.8—GLM-5.170.6%SourceNot directly comparable
CyberGym
Claude Opus 4.8—GLM-5.168.7%SourceNot directly comparable
Claw-Eval
Claude Opus 4.8—GLM-5.162.3%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceGLM-5.1—Not directly comparable
SWE-bench Pro
Claude Opus 4.869.2%SourceGLM-5.158.4%SourceClaude Opus 4.8 leads this result
SWE Multilingual
Claude Opus 4.884.4%SourceGLM-5.1—Not directly comparable
SWE Multimodal
Claude Opus 4.838.4%SourceGLM-5.1—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceGLM-5.1—Not directly comparable
cursorBench31
Claude Opus 4.858.4%SourceGLM-5.1—Not directly comparable
cursorBench32
Claude Opus 4.862.3%SourceGLM-5.1—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceGLM-5.1—Not directly comparable
NL2Repo
Claude Opus 4.8—GLM-5.142.7%SourceNot directly comparable
SWE-Rebench
Claude Opus 4.8—GLM-5.162.7%SourceNot directly comparable
Vibe Code Bench
Claude Opus 4.8—GLM-5.131.46%SourceNot directly comparable
OpenHarmony Bench
Claude Opus 4.8—GLM-5.152.3%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Claude Opus 4.893.6%SourceGLM-5.1—Not directly comparable
GPQA-D
Claude Opus 4.893.6%SourceGLM-5.186.2%SourceClaude Opus 4.8 leads this result
HLE
Claude Opus 4.857.9%SourceGLM-5.152.3%SourceClaude Opus 4.8 leads this result
HLE w/o tools
Claude Opus 4.849.8%SourceGLM-5.1—Not directly comparable
Math
USAMO 2026
Claude Opus 4.896.7%SourceGLM-5.1—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Opus 4.847.241%GLM-5.133.448%Claude Opus 4.8 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Opus 4.831.250%GLM-5.112.500%Claude Opus 4.8 leads this result
AIME26
Claude Opus 4.8—GLM-5.195.3%SourceNot directly comparable
HMMT Nov 2025
Claude Opus 4.8—GLM-5.194.0%SourceNot directly comparable
HMMT Feb 2026
Claude Opus 4.8—GLM-5.182.6%SourceNot directly comparable
MMAnswerBench
Claude Opus 4.8—GLM-5.183.8%SourceNot directly comparable
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceGLM-5.1—Not directly comparable
Multimodal
Frequently asked questions
Which is better, Claude Opus 4.8 or GLM-5.1?
Claude Opus 4.8 has the higher public score estimate, 76.45 versus 66.99, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Claude Opus 4.8 or GLM-5.1?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude Opus 4.8 or GLM-5.1?
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Opus 4.8 or GLM-5.1?
For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.0036 on GLM-5.1; repository review costs $0.325 and $0.0832; the cache-heavy agent loop costs $1.35 and $0.352. GLM-5.1 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. GLM-5.1 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.8 or GLM-5.1?
Claude Opus 4.8 has the larger documented context window: 1M, compared with 203K.
Related comparisons
Last updated August 26, 2026
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