Agentic
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- Not ranked
- Basis
- BenchAlign lane · 0 vs 0 public rows
- Reading
- Not comparable
Claude 3.5 Sonnet vs GLM-4.6
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
GLM-4.6 has the higher public score estimate, 53.94 versus 31.93, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude 3.5 Sonnet is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Claude 3.5 Sonnet and GLM-4.6 are not ranked on the public lane for agentic, so no winner is named for agentic.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude 3.5 Sonnet does not fit this workload in one request. GLM-4.6 does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate. GLM-4.6 has no comparable published API token rate.
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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 Claude 3.5 Sonnet only
2 Shared
1 GLM-4.6 only
- Shared results
- 2
- Claude 3.5 Sonnet only
- 2
- GLM-4.6 only
- 1
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- 48.8
- Estimated · #84/183
- Basis
- BenchAlign lane · 1 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- 41.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- 45.3
- Estimated · #115/181
- Basis
- BenchAlign lane · 1 vs 0 public rows
- Reading
- Not comparable
Math
Not comparable- Claude 3.5 Sonnet
- 25.7
- Unranked · 2 rankable rows
- GLM-4.6
- 27.5
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude 3.5 Sonnet
- Not ranked
- GLM-4.6
- 42.1
- #98/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude 3.5 Sonnet | GLM-4.6 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Coding | Not ranked | 48.8Estimated · #84/183 | Not comparableBenchAlign lane · 1 vs 1 public rows | Not comparable |
| Reasoning | Not ranked | 41.4Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 45.3Estimated · #115/181 | Not comparableBenchAlign lane · 1 vs 0 public rows | Not comparable |
| Math | 25.7Unranked · 2 rankable rows | 27.5Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 42.1#98/120 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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
FrontierMath v2 (Tiers 1-3)
Math
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 3.5 Sonnet
- $0.0105
- Fits in one request
- GLM-4.6
- API rate not published
- Fits in one request
GLM-4.6 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude 3.5 Sonnet
- $0.195
- Fits in one request
- GLM-4.6
- API rate not published
- Fits in one request
GLM-4.6 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude 3.5 Sonnet
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
- GLM-4.6
- API rate not published
- Does not fit in one request
- Cached-input rate unavailable
Claude 3.5 Sonnet does not fit this workload in one request. GLM-4.6 does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate. GLM-4.6 has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude 3.5 SonnetGLM-4.6
Context window
Maximum documented context; output-token limits may be lower.
Claude 3.5 Sonnet
200K
GLM-4.6
200K
API model ID
Claude 3.5 Sonnet
Not sourced
GLM-4.6
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude 3.5 Sonnet
Not published
GLM-4.6
No comparable hosted API rate
Documented inputs
Claude 3.5 Sonnet
Not sourced
GLM-4.6
Not sourced
Documented outputs
Claude 3.5 Sonnet
Not sourced
GLM-4.6
Not sourced
Provider availability
Claude 3.5 Sonnet
Not sourced
GLM-4.6
Not sourced
Reasoning profile
Claude 3.5 Sonnet
Non-Reasoning
GLM-4.6
Reasoning
Weight access
Claude 3.5 Sonnet
Proprietary
GLM-4.6
Open Weight
License
Claude 3.5 Sonnet
Proprietary
GLM-4.6
Open Weight
Release date
Claude 3.5 Sonnet
2024-06-01
GLM-4.6
2025-09-01
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
- GLM-4.6 has the higher public score estimate, 53.94 versus 31.93, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 200K.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence5 rows
Coding
Knowledge
GPQA
Claude 3.5 Sonnet59.4%SourceGLM-4.6—Not directly comparable
Math
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude 3.5 Sonnet2.069%GLM-4.63.819%GLM-4.6 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude 3.5 Sonnet0.000%GLM-4.62.128%GLM-4.6 leads this result
Frequently asked questions
Which is better, Claude 3.5 Sonnet or GLM-4.6?
GLM-4.6 has the higher public score estimate, 53.94 versus 31.93, 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 3.5 Sonnet or GLM-4.6?
Claude 3.5 Sonnet is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude 3.5 Sonnet or GLM-4.6?
Claude 3.5 Sonnet and GLM-4.6 are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude 3.5 Sonnet or GLM-4.6?
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 3.5 Sonnet or GLM-4.6?
Both models list the same context window, 200K.
Related comparisons
Last updated September 4, 2026
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