Data as of October 17, 2026 · How the score is built
Released Jan 19, 2026200K context
GLM-4.7-Flash
Decision readingGLM-4.7-Flash scores 39.1 out of 100 and ranks #145 of 224. This profile shows 4 source-displayable benchmark rows. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.
Released Jan 19, 2026 — see all recent releases
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
39.1/100
field median 49.6#145 of 224 ranked models
Public
#145of 224
Verified —
Price
Self-hosted; infrastructure cost varies
input median $0.75No comparable first-party hosted token rate
Speed
67tok/s
field median 92 tok/sFirst token 31.56 s
Context
200Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
4 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 4 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| CodingRank Not rankedWeight 20%2 benchmarksVerified | 41.1 | 2 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank Not rankedWeight 12%1 benchmarkVerified | 67.1 | 1 benchmark | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%1 benchmarkVerified | Score pending | 1 benchmark | Verified |
4 of 681 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- AgenticNot measured
- Coding2/2 verified
- ReasoningNot measured
- MultimodalNot measured
- Knowledge1/1 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- Math1/1 verified
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score59.2% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap36.8 behind | WeightDisplay only | Provider exact |
| LiveCodeBench v6 | Score64.0% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap29.2 behind | WeightDisplay only | Provider exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| GPQAGraduate-Level Google-Proof Q&A | Score75.2% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap20.8 behind | Weight3% ref. weight | Provider exact |
Math1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| AIME 2025American Invitational Mathematics Examination 2025 | Score91.6% | Versus best verified row Best verified: GPT-5.2 · 100% | Gap8.4 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 4 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 200K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Superseded
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
GLM-4.7-Flash ranks #145 of 224 on the public leaderboard with a score of 39.13/100. It does not yet have enough sourced coverage for a verified position.
GLM-4.7-Flash is a open weight model with a 200K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
4 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated October 17, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does GLM-4.7-Flash perform overall in AI benchmarks?
GLM-4.7-Flash ranks #145 out of 224 models on the public BenchAlign leaderboard, with a score of 39.13/100. Its evidence status is Estimated, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is GLM-4.7-Flash good for knowledge and understanding?
GLM-4.7-Flash has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GLM-4.7-Flash good for coding and programming?
GLM-4.7-Flash has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GLM-4.7-Flash good for mathematics?
GLM-4.7-Flash has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GLM-4.7-Flash open source?
GLM-4.7-Flash is an open-weight model from Z.AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Does GLM-4.7-Flash have full benchmark coverage on BenchLM?
No. GLM-4.7-Flash currently has 4 source-displayable rows across 681 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of GLM-4.7-Flash?
GLM-4.7-Flash has a reported context window of 200K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.