Agentic
Like-for-like- GLM-4.7
- 45.7
- Inkling
- 69.4
- Weighted basis
- 2 vs 2 rows
- Reading
- Inkling leads
GLM-4.7 vs Inkling
Updated August 29, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Inkling has the higher public score estimate, 67.02 versus 60.91, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
5 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.
Agentic work
Tool use, computer use, and multi-step task completion
Inkling
Inkling leads on the same 2 weighted benchmark rows.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Inkling
Inkling 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
The category averages use different weighted benchmark sets, so they are 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. GLM-4.7 does not fit this workload in one request. GLM-4.7 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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
8 GLM-4.7 only
5 Shared
10 Inkling only
- Shared results
- 5
- GLM-4.7 only
- 8
- Inkling only
- 10
- Like-for-like categories
- 1 / 8
2 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- GLM-4.7
- 75.4
- Inkling
- 68.6
- Weighted basis
- 3 vs 2 rows
- Reading
- Directional only
Knowledge
Directional only- GLM-4.7
- 51.8
- Inkling
- 51.6
- Weighted basis
- 3 vs 2 rows
- Reading
- Directional only
Reasoning
Not comparable- GLM-4.7
- Not measured
- Inkling
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- GLM-4.7
- 1.8
- Inkling
- 97.1
- Weighted basis
- 2 vs 1 rows
- Reading
- Not comparable
Multilingual
Not comparable- GLM-4.7
- Not measured
- Inkling
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- GLM-4.7
- Not measured
- Inkling
- 76.5
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Instruction following
Not comparable- GLM-4.7
- Not measured
- Inkling
- 79.8
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | GLM-4.7 | Inkling | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 45.7 | 69.4 | Like-for-like2 vs 2 rows | Inkling leads |
| Coding | 75.4 | 68.6 | Directional only3 vs 2 rows | Directional only |
| Knowledge | 51.8 | 51.6 | Directional only3 vs 2 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | 1.8 | 97.1 | Not comparable2 vs 1 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 76.5 | Not comparable0 vs 2 rows | Not comparable |
| Instruction following | Not measured | 79.8 | Not comparable0 vs 1 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.
BrowseComp
Agentic
Terminal-Bench 2.0
Agentic
HLE
Knowledge
SWE-bench Verified
Coding
GPQA
Knowledge
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
- GLM-4.7
- Self-hosted; infrastructure cost varies
- Fits in one request
- Inkling
- $0.00421
- Fits in one request
GLM-4.7 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GLM-4.7
- Self-hosted; infrastructure cost varies
- Fits in one request
- Inkling
- $0.10754
- Fits in one request
GLM-4.7 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GLM-4.7
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
- Inkling
- $0.159
- Fits in one request
GLM-4.7 does not fit this workload in one request. GLM-4.7 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.
SpecificationGLM-4.7Inkling
Context window
Maximum documented context; output-token limits may be lower.
GLM-4.7
200K
Inkling
1M
API model ID
GLM-4.7
Not sourced
Inkling
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GLM-4.7
No comparable hosted API rate
Inkling
$0.374 per 1M cached input tokens
Documented inputs
GLM-4.7
Not sourced
Inkling
Not sourced
Documented outputs
GLM-4.7
Not sourced
Inkling
Not sourced
Provider availability
GLM-4.7
Not sourced
Inkling
Not sourced
Reasoning profile
GLM-4.7
Reasoning
Inkling
Hybrid
Weight access
GLM-4.7
Open Weight
Inkling
Open Weight
License
GLM-4.7
Open Weight
Inkling
Open Weight
Release date
GLM-4.7
2025-10-01
Inkling
2026-07-15
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
- Inkling has the higher public score estimate, 67.02 versus 60.91, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Inkling has the larger documented window (1M).
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 evidence23 rows
Agentic
Terminal-Bench 2.0
GLM-4.741%SourceInkling63.8%SourceInkling leads this result
BrowseComp
GLM-4.752%SourceInkling77.1%SourceInkling leads this result
VITA-Bench
GLM-4.715.5%SourceInkling—Not directly comparable
Gert Labs
GLM-4.739.95%SourceInkling—Not directly comparable
MCP Atlas
GLM-4.7—Inkling74.1%SourceNot directly comparable
Coding
SWE-bench Verified
GLM-4.773.8%SourceInkling77.6%SourceInkling leads this result
LiveCodeBench
GLM-4.784.9%SourceInkling—Not directly comparable
SWE-Rebench
GLM-4.758.7%SourceInkling—Not directly comparable
SWE-bench Pro
GLM-4.7—Inkling54.3%SourceNot directly comparable
Terminal-Bench 2.0
GLM-4.7—Inkling63.8%SourceNot directly comparable
Knowledge
GPQA
GLM-4.785.7%SourceInkling87.9%SourceInkling leads this result
MMLU-Pro
GLM-4.784.3%SourceInkling—Not directly comparable
HLE
GLM-4.724.8%SourceInkling46%SourceInkling leads this result
GPQA-D
GLM-4.7—Inkling87.9%SourceNot directly comparable
HLE w/o tools
GLM-4.7—Inkling30%SourceNot directly comparable
Math
Multimodal
Instruction following
IFBench
GLM-4.7—Inkling79.8%SourceNot directly comparable
Frequently asked questions
Which is better, GLM-4.7 or Inkling?
Inkling has the higher public score estimate, 67.02 versus 60.91, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, GLM-4.7 or Inkling?
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, GLM-4.7 or Inkling?
Inkling leads the like-for-like agentic tasks comparison across 2 shared weighted benchmark rows.
Which costs less, GLM-4.7 or Inkling?
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, GLM-4.7 or Inkling?
Inkling has the larger documented context window: 1M, compared with 200K.
Related comparisons
Last updated August 29, 2026
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