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
#131
by active users
Active users
100
All time
Adoption
4.0%
of 2,470 accounts
Tokens
3.7B
cache included
Est. cost
$859
at public list prices
First seen
Jan 19, 2026
in any submission

Oct 10, 2024 – Nov 14, 2026 (UTC)2,470 accounts100% of tokens from an identified modelData through Nov 14, 2026, 03:08 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 14, 2026

Daily active users for GLM-4.7 Flash, Oct 10, 2024 to Nov 14, 2026. Peak 6. Use the left and right arrow keys to read each day.630
Show daily values
Daily active users and tokens for GLM-4.7 Flash
Date (UTC)Active usersTokens
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Jan 1, 202500
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Dec 30, 202500
Dec 31, 202500
Jan 1, 202600
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Jan 19, 202626.7M
Jan 20, 20266107.8M
Jan 21, 2026652.2M
Jan 22, 202651.7M
Jan 23, 2026620.8M
Jan 24, 202662.3M
Jan 25, 202652.1M
Jan 26, 20262701K
Jan 27, 2026418M
Jan 28, 2026433.1M
Jan 29, 2026638.1M
Jan 30, 2026482.9M
Jan 31, 2026257.5M
Feb 1, 2026237.8M
Feb 2, 2026514.5M
Feb 3, 202668.2M
Feb 4, 202645.2M
Feb 5, 202638.2M
Feb 6, 202645.4M
Feb 7, 202645.1M
Feb 8, 2026218.2M
Feb 9, 2026535.9M
Feb 10, 202641.7M
Feb 11, 202659.4M
Feb 12, 20263670K
Feb 13, 202631.7M
Feb 14, 20262239K
Feb 15, 2026130.3K
Feb 16, 202600
Feb 17, 202621.6M
Feb 18, 20262898K
Feb 19, 2026426.3M
Feb 20, 2026524.3M
Feb 21, 2026312M
Feb 22, 2026622.7M
Feb 23, 2026410.2M
Feb 24, 2026514.8M
Feb 25, 20265114.8M
Feb 26, 2026534.6M
Feb 27, 2026317.1M
Feb 28, 2026331.5M
Mar 1, 2026235.7M
Mar 2, 2026314.9M
Mar 3, 20264140.7M
Mar 4, 2026119.7M
Mar 5, 2026231.3M
Mar 6, 2026129.4M
Mar 7, 2026224M
Mar 8, 2026468M
Mar 9, 2026141.8M
Mar 10, 2026135.9M
Mar 11, 2026252M
Mar 12, 20262320.8M
Mar 13, 20263760.6M
Mar 14, 2026275.8M
Mar 15, 2026258.3M
Mar 16, 2026355.7M
Mar 17, 20263163.9M
Mar 18, 2026261.1M
Mar 19, 2026231.7M
Mar 20, 20262131.7M
Mar 21, 2026296.9M
Mar 22, 20263222.1M
Mar 23, 2026377.1M
Mar 24, 2026123.8M
Mar 25, 202600
Mar 26, 202600
Mar 27, 202600
Mar 28, 2026113.5K
Mar 29, 202600
Mar 30, 2026131.1K
Mar 31, 20261625K
Apr 1, 202625.9M
Apr 2, 2026129.2M
Apr 3, 2026113.2M
Apr 4, 202614.7M
Apr 5, 2026243.3M
Apr 6, 202644.2M
Apr 7, 202600
Apr 8, 2026237.7K
Apr 9, 2026331.4M
Apr 10, 2026110.1M
Apr 11, 2026121.1M
Apr 12, 202617M
Apr 13, 202625.6M
Apr 14, 202615.5M
Apr 15, 202622.3M
Apr 16, 202625.6M
Apr 17, 202611.6M
Apr 18, 202625.6M
Apr 19, 202633.4M
Apr 20, 202631.6M
Apr 21, 202621.7M
Apr 22, 202623.4M
Apr 23, 2026159.2K
Apr 24, 20262966K
Apr 25, 20261999K
Apr 26, 202600
Apr 27, 202600
Apr 28, 202600
Apr 29, 20261818K
Apr 30, 202600
May 1, 20261936K
May 2, 202600
May 3, 2026133.5K
May 4, 202600
May 5, 20261985K
May 6, 202632.8M
May 7, 202611.9M
May 8, 202600
May 9, 202600
May 10, 202611.3M
May 11, 202614.8M
May 12, 202600
May 13, 20261686K
May 14, 2026182.8K
May 15, 202600
May 16, 202631.4M
May 17, 202612.3M
May 18, 202612.5M
May 19, 20261851K
May 20, 20261779K
May 21, 20261860K
May 22, 20261428K
May 23, 202600
May 24, 20261667K
May 25, 20261290K
May 26, 20262542K
May 27, 20261311K
May 28, 20262742K
May 29, 20261284K
May 30, 20261750K
May 31, 20262841K
Jun 1, 202611.6M
Jun 2, 202611.1M
Jun 3, 202611.4M
Jun 4, 20261644K
Jun 5, 2026134.4K
Jun 6, 20261972K
Jun 7, 202600
Jun 8, 202600
Jun 9, 2026112.7K
Jun 10, 20262101K
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Jun 20, 2026110.4K
Jun 21, 202611.1M
Jun 22, 202622.3M
Jun 23, 2026111.8K
Jun 24, 202600
Jun 25, 202625.1M
Jun 26, 20262544K
Jun 27, 2026239.5K
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Jun 29, 202619.2K
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Jul 5, 202600
Jul 6, 2026122.8K
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Jul 9, 20261608K
Jul 10, 20262133K
Jul 11, 2026125.9K
Jul 12, 20261118K
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Jul 14, 202600
Jul 15, 202600
Jul 16, 20261859K
Jul 17, 202600
Jul 18, 20261554K
Jul 19, 2026117.4K
Jul 20, 2026112K
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Jul 23, 202600
Jul 24, 2026166.4K
Jul 25, 2026112.2K
Jul 26, 202611.2M
Jul 27, 20262165K
Jul 28, 202600
Jul 29, 202600
Jul 30, 202600
Jul 31, 2026115K
Aug 1, 202600
Aug 2, 202600
Aug 3, 2026120.6K
Aug 4, 202600
Aug 5, 20262253K
Aug 6, 202624.8M
Aug 7, 202600
Aug 8, 2026197.3K
Aug 9, 2026197.7K
Aug 10, 2026172K
Aug 11, 202600
Aug 12, 202600
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Aug 15, 202600
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Aug 20, 20261438K
Aug 21, 20261102K
Aug 22, 202600
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Aug 27, 202600
Aug 28, 202600
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Sep 1, 202611K
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Sep 3, 202600
Sep 4, 202600
Sep 5, 202600
Sep 6, 20261264K
Sep 7, 202600
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Sep 12, 202600
Sep 13, 202613.3M
Sep 14, 202600
Sep 15, 202600
Sep 16, 20261933K
Sep 17, 202600
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Sep 28, 202600
Sep 29, 202600
Sep 30, 202600
Oct 1, 202600
Oct 2, 202600
Oct 3, 2026149.9K
Oct 4, 202600
Oct 5, 20261226K
Oct 6, 202600
Oct 7, 202600
Oct 8, 202600
Oct 9, 2026142K
Oct 10, 2026193.2K
Oct 11, 202600
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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, 2026218.9K
Nov 10, 202617.4K
Nov 11, 2026121.3K
Nov 12, 2026124.2K
Nov 13, 202600
Nov 14, 202600

Token mix

How the 3.7B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input64%
  • Output0.5%
  • Cache read35%
  • Cache write<0.1%
  • Reasoning<0.1%

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. OpenCode68% of this model's tokens69active users
  2. OpenClaw27% of this model's tokens7active users
  3. Claude Code4.4% of this model's tokens10active users
  4. Pi0.3% of this model's tokens9active users
  5. cc-mirror/zaicc0.3% of this model's tokens1active users
  6. Oh My Pi0.2% of this model's tokens3active users
  7. Hermes Agent0.2% of this model's tokens4active users
  8. Cline<0.1% of this model's tokens1active users
  9. Kilo<0.1% of this model's tokens1active users
  10. LM Studio<0.1% of this model's tokens5active 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
35% cache reads
At the community mix
$0
Est. per 1M tokens
93% cache reads
3:1 input/output blend
$0
Per 1M tokens at list prices
No cache

Cache reads were 35% of GLM-4.7 Flash tokens across all time and 93% 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 across all time.
  • The community mix is the tokens of every identified model across all time.
  • 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. 1alexmhtop@alexmhtop1.7Btokens$754est. cost16active days$754 est. cost · 16 active days
  2. 2addison@addidotlol973.1Mtokens$48est. cost35active days$48 est. cost · 35 active days
  3. 3Mikal@mikalv287.4Mtokens$16est. cost13active days$16 est. cost · 13 active days
  4. 4jianqiang.cao@vacat220.6Mtokens$8est. cost13active days$8 est. cost · 13 active days
  5. 5Code_G@codeg-dev202.1Mtokens$15est. cost64active days$15 est. cost · 64 active days
  6. 6Marco Frömbgen@mfroembgen150.5Mtokens$6est. cost3active days$6 est. cost · 3 active days
  7. 7nagoodman@nagoodman41.5Mtokens<$1est. cost2active days<$1 est. cost · 2 active days
  8. 8YeonGyu-Kim@code-yeongyu20.4Mtokens$1est. cost5active days$1 est. cost · 5 active days
  9. 9DevNewbie1826@DevNewbie182615Mtokens<$1est. cost1active days<$1 est. cost · 1 active days
  10. 10iz@islee2352013.7Mtokens<$1est. cost10active days<$1 est. cost · 10 active days

More from Z.ai

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

  1. GLM-5.222% adoption554active users
  2. GLM-5.117% adoption431active users
  3. GLM-5.3 Flash17% adoption412active users
  4. GLM-5.315% adoption364active users
  5. GLM-4.714% adoption353active users
  6. GLM-4.7 Free13% adoption328active 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