Z.ai, released Dec 22, 2025

GLM-4.7price, context, benchmarks and release details

Provisional: not enough results to rank yet Open weights 69% confidence 69 percent, Medium confidence, 3 of 7 expected sources in
61.3
SI Score
#57 of 142 ranked models
Input, per 1M tokens
$0.60Z.ai API pricingOfficial Z.ai global Standard uncached token rate; coding-plan subscriptions, cache and Batch excluded Retrieved Oct 9, 2026 · factual citation
Open source ↗
Output, per 1M tokens
$2.20Z.ai API pricingOfficial Z.ai global Standard uncached token rate; coding-plan subscriptions, cache and Batch excluded Retrieved Oct 9, 2026 · factual citation
Open source ↗
Context window
205Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
131Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Dec 22, 2025models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 53.6
Math (weight 15 percent) 83.3
Preference (weight 15 percent) 76.4
Reasoning (weight 30 percent) 83.3

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 06:15 UTC.

Around it on the leaderboard

  1. 55 GPT-6 Luna 61.6
  2. 56 Qwen3.6 Plus 61.6
  3. 57 GLM-4.7 61.3
  4. 58 GPT-5.4 Pro 61.3
  5. 59 Nemotron 3 Ultra 550B A55B 61.2

Full leaderboard

Benchmark results

5 benchmarks, 5 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

GPQA Diamondreasoning 83.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 29, 2026 Retrieved Oct 9, 2026 · CC-BY
Open source ↗
83.3
OTIS Mock AIME 2024–2025math 83.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 29, 2026 Retrieved Oct 9, 2026 · CC-BY
Open source ↗
83.3
SWE-bench Verifiedcoding 73.8%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant] Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
73.8
Terminal-Benchcoding 33.4%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
33.4
LMArena Textpreference 1435.2 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗
76.4

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Yesmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
textmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
55% of expected source weight

Reported (3)

  • Epoch AI BenchmarkingOct 8, 2026
  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (4)

  • ARC Prize13% of weight
  • Humanity’s Last Exam13% of weight
  • LiveBench13% of weight
  • Terminal-Bench6% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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