GLM-5.1

GLM-5.1 is Z.AI's flagship coding model, built for long-horizon software tasks that require autonomous planning, bug fixing, and iterative refinement.

input · usd / 1m tok

$1.40

output · usd / 1m tok

$4.40

context window

200ktokens

modalities · in → out

takes text in, gives text out

pricing

base api ratesusd per 1m tokens

input
$1.40
output
$4.40
cache read
$0.26

providers

Z.AI hosts GLM-5.1. Impossibl routes your request intelligently and handles failover automatically when a provider is down.

  • Z.AI

specifications

takes text in, gives text outzai/glm-5.1

  • creatorZ.AI
  • model typeText generation
  • context window200,000 tokens
  • maximum outputnot published
  • input

    takes text in, gives text out

  • outputtext
  • tool callingnot verified
  • releasedapr 7, 2026
  • endpoint/v1/chat/completions

unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports. see the model documentation for integration details.

try it · your prompt, this model, live

# responses API
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["IMPOSSIBL_API_KEY"],
    base_url="https://api.impossibl.com/v1",
)

resp = client.responses.create(
    model="zai/glm-5.1",
    input="",
)
print(resp.output_text)

edit the prompt, then run

benchmarks

intelligence index

26.4#40 of 90 models on the gateway

  1. coding index55.8#39 of 60
  2. agentic index25.2#32 of 49
  3. omniscience0.8#35 of 86
  4. gpqa86.8%#45 of 88
  5. humanity’s last exam30.1%#43 of 89
  6. terminal-bench v2.161.8%#36 of 57
  1. Tau297.7%
  2. GPQA86.8%
  3. IFBench76.3%
  4. AA-LCR73.7%
  5. Terminal-Bench v2.161.8%
  6. SciCode44.8%
  7. Terminal-Bench Hard43.2%
  8. ITBench40.3%
  9. Humanity’s Last Exam30.1%
  10. AutomationBench Partial20.3%
  11. Tau Banking13.6%
  12. GDP.pdf All-pass8.4%
  13. CritPt4.6%
  14. Terminal-Bench v4.02.0%
  • Intelligence Index26.45
  • Omniscience Index0.85
  • GDPval Elo1180.01
  • coding index (API)55.8
  • agentic index (API)25.2
  • intelligence index (API)26.4

view source ↗all source data and breakdowns (json) ↗

each configuration is listed separately; these evaluations describe the tested model configuration, and performance and costs can differ on impossibl. unmeasured scores are omitted and api values keep their source units. last checked 2026-09-11.

compare GLM-5.1 with other models

frontier labs and open weights, best-ranked firstusd / 1m tok · in / out

impossibl models --all →

frequently asked questions

What is GLM-5.1?

GLM-5.1 is Z.AI's flagship coding model, built for long-horizon software tasks that require autonomous planning, bug fixing, and iterative refinement. Where earlier GLM models were designed around minute-level interactions, GLM-5.1 can work independently and continuously for hours in a single run.

How much does GLM-5.1 cost?

GLM-5.1 costs $1.40 per million input tokens and $4.40 per million output tokens through the Impossibl API. Cache reads cost $0.26 per million tokens. All rates are in USD.

view the pricing table ↑

What is the context length of GLM-5.1?

GLM-5.1 has a 200,000-token context window through the Impossibl API.

What inputs and outputs does GLM-5.1 support?

GLM-5.1 accepts text as input. GLM-5.1 returns text.

How do I use GLM-5.1 through an API?

GLM-5.1 is available through the Impossibl API. Use zai/glm-5.1 as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.

follow the api quickstart →

When was GLM-5.1 released?

Z.AI released GLM-5.1 on April 7, 2026.

this page describes GLM-5.1 as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes. model descriptions and release dates, where available, use the creator sources linked under the answers above.

view the source catalog ↗model as markdown ↗report a correction →