Knowledge
Directional only- GLM-5.2
- 60.7
- Supported · #35/183
- Interfaze Beta
- 48.6
- Estimated · #91/183
- Basis
- BenchAlign lane · 6 vs 3 public rows
- Reading
- Directional only
GLM-5.2 vs Interfaze Beta
Updated September 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality 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.
Chat turn cost
1K fresh input + 500 output tokens
Interfaze Beta
Interfaze Beta has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
GLM-5.2
GLM-5.2 has the lower estimated token cost for this stated workload. GLM-5.2 has no published cached-input rate, so cached tokens use its listed input rate. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
GLM-5.2
GLM-5.2 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
Interfaze Beta 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
Interfaze Beta is 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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
23 GLM-5.2 only
2 Shared
7 Interfaze Beta only
- Shared results
- 2
- GLM-5.2 only
- 23
- Interfaze Beta only
- 7
- Like-for-like categories
- 0 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Agentic
Not comparable- GLM-5.2
- 58.5
- Supported · #29/153
- Interfaze Beta
- Not ranked
- Basis
- BenchAlign lane · 6 vs 0 public rows
- Reading
- Not comparable
Coding
Not comparable- GLM-5.2
- 61.0
- Supported · #19/152
- Interfaze Beta
- Not ranked
- Basis
- BenchAlign lane · 8 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GLM-5.2
- 74.8
- Unranked · 2 rankable rows
- Interfaze Beta
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- GLM-5.2
- 80.7
- Unranked · 4 rankable rows
- Interfaze Beta
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GLM-5.2
- Not ranked
- Interfaze Beta
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GLM-5.2
- Not ranked
- Interfaze Beta
- 27.5
- Unranked · 5 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GLM-5.2
- 89.8
- #22/123
- Interfaze Beta
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | GLM-5.2 | Interfaze Beta | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 60.7Supported · #35/183 | 48.6Estimated · #91/183 | Directional onlyBenchAlign lane · 6 vs 3 public rows | Directional only |
| Agentic | 58.5Supported · #29/153 | Not ranked | Not comparableBenchAlign lane · 6 vs 0 public rows | Not comparable |
| Coding | 61.0Supported · #19/152 | Not ranked | Not comparableBenchAlign lane · 8 vs 1 public rows | Not comparable |
| Reasoning | 74.8Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 80.7Unranked · 4 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 27.5Unranked · 5 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | 89.8#22/123 | Not ranked | 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.
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-5.2
- $0.0036
- Fits in one request
- Interfaze Beta
- $0.00325
- Fits in one request
Interfaze Beta has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GLM-5.2
- $0.0832
- Fits in one request
- Interfaze Beta
- $0.0855
- Fits in one request
GLM-5.2 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GLM-5.2
- $0.352
- Fits in one request
- Cached input priced at the published list-input rate
- Interfaze Beta
- $0.365
- Fits in one request
- Cached input priced at the published list-input rate
GLM-5.2 has the lower modeled cost
GLM-5.2 has no published cached-input rate, so cached tokens use its listed input rate. Interfaze Beta 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.
SpecificationGLM-5.2Interfaze Beta
Context window
Maximum documented context; output-token limits may be lower.
GLM-5.2
1M
Interfaze Beta
1M
API model ID
GLM-5.2
Not sourced
Interfaze Beta
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GLM-5.2
Not published
Interfaze Beta
Not published
Documented inputs
GLM-5.2
Not sourced
Interfaze Beta
Not sourced
Documented outputs
GLM-5.2
Not sourced
Interfaze Beta
Not sourced
Provider availability
GLM-5.2
Not sourced
Interfaze Beta
Not sourced
Reasoning profile
GLM-5.2
Reasoning
Interfaze Beta
Reasoning
Weight access
GLM-5.2
Open Weight
Interfaze Beta
Proprietary
License
GLM-5.2
Open Weight
Interfaze Beta
Proprietary
Release date
GLM-5.2
2026-06-16
Interfaze Beta
2026-05-11
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.0832 vs $0.0855. Cache-heavy agent loop: $0.352 vs $0.365.
- Context tradeoff
- Both models list 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 evidence32 rows
Agentic
Terminal-Bench 3.0
GLM-5.24.6%SourceInterfaze Beta—Not directly comparable
Terminal-Bench 2.0
GLM-5.281%SourceInterfaze Beta—Not directly comparable
MCP Atlas
GLM-5.276.8%SourceInterfaze Beta—Not directly comparable
Toolathlon
GLM-5.248.2%SourceInterfaze Beta—Not directly comparable
ResearchClawBench
GLM-5.220.7%SourceInterfaze Beta—Not directly comparable
Terminal-Bench 2.1 (Vals)
GLM-5.267.8%SourceInterfaze Beta—Not directly comparable
Coding
SWE-bench Pro
GLM-5.262.1%SourceInterfaze Beta—Not directly comparable
NL2Repo
GLM-5.248.9%SourceInterfaze Beta—Not directly comparable
Terminal-Bench 2.0
GLM-5.281.0%SourceInterfaze Beta—Not directly comparable
ProgramBench
GLM-5.263.7%SourceInterfaze Beta—Not directly comparable
cursorBench32
GLM-5.255.0%SourceInterfaze Beta—Not directly comparable
OpenHarmony Bench
GLM-5.258.4%SourceInterfaze Beta—Not directly comparable
LiveCodeBench (Vals)
GLM-5.269.5%SourceInterfaze Beta—Not directly comparable
SWE-bench (Vals)
GLM-5.282.8%SourceInterfaze Beta—Not directly comparable
Spider 2.0-Lite
GLM-5.2—Interfaze Beta52.9%SourceNot directly comparable
Reasoning
CritPt
GLM-5.220.9%SourceInterfaze Beta—Not directly comparable
Knowledge
GPQA
GLM-5.291.2%SourceInterfaze Beta89.9%SourceGLM-5.2 leads this result
GPQA-D
GLM-5.291.2%SourceInterfaze Beta89.9%SourceGLM-5.2 leads this result
HLE
GLM-5.254.7%SourceInterfaze Beta—Not directly comparable
HLE w/o tools
GLM-5.240.5%SourceInterfaze Beta—Not directly comparable
GPQA Diamond (Vals)
GLM-5.285.6%SourceInterfaze Beta—Not directly comparable
MMLU-Pro (Vals)
GLM-5.286.7%SourceInterfaze Beta—Not directly comparable
MMMLU
GLM-5.2—Interfaze Beta90.9%SourceNot directly comparable
Math
Multimodal
Instruction following
SOB Value Acc
GLM-5.2—Interfaze Beta79.5%SourceNot directly comparable
Frequently asked questions
Which is better, GLM-5.2 or Interfaze Beta?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, GLM-5.2 or Interfaze Beta?
Interfaze Beta is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, GLM-5.2 or Interfaze Beta?
Interfaze Beta is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GLM-5.2 or Interfaze Beta?
For the stated presets, chat costs $0.0036 on GLM-5.2 and $0.00325 on Interfaze Beta; repository review costs $0.0832 and $0.0855; the cache-heavy agent loop costs $0.352 and $0.365. GLM-5.2 has no published cached-input rate, so cached tokens use its listed input rate. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, GLM-5.2 or Interfaze Beta?
Both models list the same context window, 1M.
Related comparisons
Last updated September 14, 2026
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