GLM 5V Turbo
Z.ai · released Apr 1, 2026
GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, excels at long-horizon planning, complex coding,...
Specification
- Context window
- 203K
- Max output
- 131K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- No
- Uptime
- 99.1%
Intelligence
35.3
82th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
37 t/s
Median across providers
Latency
4.96s
Time to first token
Cost per task
$0.38
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- τ²-bench (Telecom)98.5%
- GPQA Diamond80.9%
- AA-LCR (long context)65.7%
- IFBench61.1%
- SciCode43.5%
- Terminal-Bench Hard32.6%
- Humanity's Last Exam17.1%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| τ²-bench (Telecom) | 98.5% |
| GPQA Diamond | 80.9% |
| AA-LCR (long context) | 65.7% |
| IFBench | 61.1% |
| SciCode | 43.5% |
| Terminal-Bench Hard | 32.6% |
| Humanity's Last Exam | 17.1% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Kimi K2.5Moonshot AI36.0
- Claude Opus 4.5Anthropic35.6
- GPT-5.1-CodexOpenAI35.6
- GLM 5V TurboZ.ai35.3
- GPT-5OpenAI35.3
- Qwen3.5-27BQwen34.6
- M2.5MiniMax34.5
- GLM 4.7Z.ai34.5
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Kimi K2.5 | 36.0 |
| Claude Opus 4.5 | 35.6 |
| GPT-5.1-Codex | 35.6 |
| GLM 5V Turbo | 35.3 |
| GPT-5 | 35.3 |
| Qwen3.5-27B | 34.6 |
| M2.5 | 34.5 |
| GLM 4.7 | 34.5 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $1.2
- Output / 1M tokens
- $4
- Cached input / 1M
- $0.24
- Blended 3:1
- $1.9
One task, estimated
$0.38
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.
Arena
Head-to-head generation quality
Elo from pairwise judgements, broken out by the kind of thing the model was asked to build.
- Overall Elo
- 1,265
- Win rate
- 54.2%
- Strongest at
- 3D scenes
- Tournaments
- 10,971
Elo by category
Dot position on a 1,175–1,275 scale · Elo has no meaningful zero
- 1,265
- 1,261
- 1,253
- 1,248
- 1,224
- 1,197
- 1,192
- 1,190
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| 3D scenes | 1265 | 54.2% |
| Game development | 1261 | 54.0% |
| Websites | 1253 | 50.5% |
| UI components | 1248 | 50.5% |
| Data visualisation | 1224 | 48.0% |
| SVG | 1197 | 51.0% |
| Mobile apps | 1192 | 50.5% |
| Full-stack apps | 1190 | 52.3% |