GLM-4.7 Flash

Z.aiKey glm-4.7-flashAlso reported as hf:zai-org/glm-4.7-flash, z-ai/glm-4.7-flash, zai-org/glm-4.7-flash, zhipuai/glm-4.7-flash, @cf/zai-org/glm-4.7-flash, workers-ai/@cf/zai-org/glm-4.7-flash

Rank
#226
by active users
Active users
4
Up 2 from 2 active users in the previous 30 days. vs previous 30 days
Adoption
0.4%
of 957 accounts
Tokens
250K
cache included
Est. cost
<$1
at public list prices
First seen
Jan 19, 2026
in any submission

Oct 15 – Nov 13, 2026 (UTC)957 accounts100% of tokens from an identified modelData through Nov 13, 2026, 02:09 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 13, 2026

Daily active users for GLM-4.7 Flash, Oct 15, 2026 to Nov 13, 2026. Peak 1. Use the left and right arrow keys to read each day.110
Show daily values
Daily active users and tokens for GLM-4.7 Flash
Date (UTC)Active usersTokens
Oct 15, 202600
Oct 16, 202600
Oct 17, 20261801
Oct 18, 202600
Oct 19, 202600
Oct 20, 202600
Oct 21, 2026143.5K
Oct 22, 202600
Oct 23, 2026111.9K
Oct 24, 2026169.4K
Oct 25, 202600
Oct 26, 202600
Oct 27, 202600
Oct 28, 202600
Oct 29, 202600
Oct 30, 202600
Oct 31, 202600
Nov 1, 202616K
Nov 2, 2026113.8K
Nov 3, 202614.2K
Nov 4, 2026117.2K
Nov 5, 2026124.5K
Nov 6, 2026113.3K
Nov 7, 202611.4K
Nov 8, 202615.3K
Nov 9, 2026110.1K
Nov 10, 202617.4K
Nov 11, 2026121.3K
Nov 12, 202600
Nov 13, 202600

Token mix

How the 250K tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input46%
  • Output40%
  • Cache read14%
  • Cache write0%
  • Reasoning0.2%

Agents that carry GLM-4.7 Flash

Each agent's share of this model's tokens, and how many accounts used the model through it.

  1. OpenCode50% of this model's tokens2active users
  2. Hermes Agent50% of this model's tokens1active users
  3. Pi0.3% of this model's tokens1active users

Benchmarks

The best result for GLM-4.7 Flash in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.

All benchmarks
  • GPQA DiamondReasoning · Epoch AI
    60.5%
    Rank #123 of 160 matched modelsNo conditions reportedRun date Aug 30, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

    Show 1 more result with other run conditionsHide the other results
    • Listed as glm-4.7-flash_none
      45.1%
      No reasoningRun date Aug 30, 2026Source: epoch.ai (opens in a new tab)

Not evaluated: Epoch Capabilities Index, Humanity's Last Exam, FrontierMath Tiers 1–3 (v2), SimpleQA Verified, Terminal-Bench 4.1, CursorBench, DeepSWE, FrontierSWE, Agent Arena, WebDev Arena. A missing result is not a score of zero.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Z.AI is the lab's own API and the reference price for the estimates below.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At this model's mix
$0
Est. per 1M tokens
14% cache reads
At the community mix
$0
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$0
Per 1M tokens at list prices
No cache

Cache reads were 14% of GLM-4.7 Flash tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • Z.AI list prices per 1M tokens: input $0, output $0, cache read $0, cache write $0.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
  • The community mix is the tokens of every identified model in the last 30 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.

List prices by provider

  • Z.AIReferenceglm-4.7-flash
    $0 input per 1M tokens$0 output per 1M tokens$0 cache read per 1M tokens$0 cache write per 1M tokens200K tokens of context
  • Amazon Bedrockzai.glm-4.7-flash
    $0.07 input per 1M tokens$0.40 output per 1M tokensCache read not listedCache write not listed203K tokens of context
  • OpenRouterz-ai/glm-4.7-flash
    $0.06 input per 1M tokens$0.40 output per 1M tokensCache read not listedCache write not listed200K tokens of context
  • Vercel AI Gatewayzai/glm-4.7-flash
    $0.07 input per 1M tokens$0.40 output per 1M tokensCache read not listedCache write not listed200K tokens of context
  • Deep Infrazai-org/GLM-4.7-Flash
    $0.06 input per 1M tokens$0.40 output per 1M tokens$0.01 cache read per 1M tokensCache write not listed203K tokens of context

Specs

From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
200K tokens
Max output
131K tokens
Input
Text
Output
Text
Knowledge cutoff
Apr 2025
Release date
Jan 19, 2026
Open weights
Yes
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used GLM-4.7 Flash most in this period, by tokens. Hidden accounts are never listed.

  1. 1rharmanca@rharmanca125Ktokens—est. cost11active daysno price · 11 active days
  2. 2Rupreet Gujral@rupreetg81.3Ktokens—est. cost2active daysno price · 2 active days
  3. 3Joosung Park@hyperlapse12243.5Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  4. 4BlockedPath @BlockedPath801tokens<$1est. cost1active days<$1 est. cost · 1 active days

More from Z.ai

Other Z.ai models in the same period, by active users.

  1. GLM-5.3 Flash18% adoption168active users
  2. GLM-5.314% adoption131active users
  3. GLM-5.3 Flash Free8.9% adoption85active users
  4. GLM-5 3 Flash1.5% adoption14active users
  5. GLM-5.21.4% adoption13active users
  6. GLM-5 30.7% adoption7active users
All models

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Nov 12, 2026 · Data through Nov 9, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • models.devSpecs and list prices per provider.MIT · Retrieved Nov 12, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count