SI Index Data as of Oct 9, 2026

GLM-4.5V: Price, Context, Benchmarks, and Release Details

Z.ai provisional listing open weights · first seen Oct 8, 2026 · score computed Oct 9, 2026, 01:09 UTC
41.6
SI Score (method si-v3-retained-evidence-2)
37% confidence 37 percent, Low confidence — 2 of 7 expected sources in
Coverage 30% of expected source weight · 100% confidence at 80% coverage

Pillar breakdown

Coding (weight 40 percent) 5.3
Math (weight 15 percent) —
Preference (weight 15 percent) 66.0
Reasoning (weight 30 percent) —

Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.

Facts

Input price / 1M
$0.60models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://docs.z.ai/guides/overview/pricing. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; zai/glm-4.5v Retrieved Oct 9, 2026 · MIT
Open source ↗
Output price / 1M
$1.80models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://docs.z.ai/guides/overview/pricing. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; zai/glm-4.5v Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
64Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
16.4Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Aug 11, 2025models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Open weights
Yesmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, image, videomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

Benchmark results

2 results
Benchmark Raw result Normalized (0–100) Pillar
lmarena text 1332.8 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 		66.0 preference
terminal bench 5.3%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Apr 29, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗ 		5.3 coding

Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.

Sources: in and pending

in Reported (2)

  • Official model cards via models.dev · arrived Oct 8, 2026
  • LMArena / Arena · arrived Oct 8, 2026

pending Awaiting (5)

  • ARC Prize · carries 13% of expected weight
  • Epoch AI Benchmarking · carries 25% of expected weight
  • Humanity’s Last Exam · carries 13% of expected weight
  • LiveBench · carries 13% of expected weight
  • Terminal-Bench · carries 6% of expected weight

The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.