# GLM-5 Usage, Cost & Rank | OpenCode Data

> GLM-5 had 0% of tokens across OpenCode over the past two months. GLM-5 costs $1.00 per 1M input tokens and $3.20 per 1M output tokens.

General GLM flagship for coding, analysis, and tool-heavy engineering workflows

- Page: https://opencode.ai/data/zhipuai/glm-5
- JSON: https://opencode.ai/data/zhipuai/glm-5.json
- Model ID: zhipuai/glm-5
- Lab: Zhipu
- Updated: 2026-09-20T18:43:53.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 205K |
| Max output | 131K |
| Knowledge cutoff | - |
| Release date | 2026-02-12 |
| Input modalities | text |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | Yes |
| Weights | [Hugging Face](https://huggingface.co/zai-org/GLM-5) |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $1.00 | $3.20 | $0.20 | $0.00 |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | Unranked |
| Tokens | 30B |
| Share of all tokens | 0% |
| Change vs previous 2 months | -42% |
| Unique users | 80K |
| Completed sessions | 40,409 |
| Average tokens per session | 752K |
| Average cost per session | $0.3419 |
| Total spend | $13,814 |
| Input tokens served from cache | 77.5% |
| Weekly retention | 60.9% |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-08 | 275M | 988 | 14 |
| 2026-08-09 | 459M | 2.6K | 30 |
| 2026-08-10 | 459M | 4.1K | 158 |
| 2026-08-11 | 584M | 6.5K | 19 |
| 2026-08-12 | 609M | 4.5K | 0 |
| 2026-08-13 | 776M | 3.6K | 0 |
| 2026-08-14 | 717M | 3.1K | 1 |
| 2026-08-15 | 394M | 2.7K | 0 |
| 2026-08-16 | 486M | 2.6K | 0 |
| 2026-08-17 | 858M | 3K | 0 |
| 2026-08-18 | 1.3B | 2.5K | 34 |
| 2026-08-19 | 1.2B | 2.5K | 181 |
| 2026-08-20 | 1.1B | 2.3K | 132 |
| 2026-08-21 | 955M | 2.3K | 132 |
| 2026-08-22 | 485M | 1.9K | 45 |
| 2026-08-23 | 427M | 1.8K | 55 |
| 2026-08-24 | 893M | 2.2K | 43 |
| 2026-08-25 | 805M | 2.3K | 87 |
| 2026-08-26 | 652M | 2.2K | 182 |
| 2026-08-27 | 1.1B | 2.3K | 543 |
| 2026-08-28 | 4.7B | 2.3K | 422 |
| 2026-08-29 | 5.3B | 1.9K | 261 |
| 2026-08-30 | 412M | 1.5K | 181 |
| 2026-08-31 | 581M | 2.4K | 1,117 |
| 2026-09-01 | 545M | 2.4K | 843 |
| 2026-09-02 | 517M | 2.1K | 647 |
| 2026-09-03 | 2.1B | 2.1K | 848 |
| 2026-09-04 | 469M | 1.9K | 1,174 |
| 2026-09-05 | 200M | 1.7K | 1,321 |
| 2026-09-06 | 395M | 1.6K | 1,570 |
| 2026-09-07 | 304M | 1.9K | 2,935 |
| 2026-09-08 | 293M | 1.6K | 2,901 |
| 2026-09-09 | 47M | 643 | 2,423 |
| 2026-09-10 | 0 | 0 | 2,761 |
| 2026-09-11 | 0 | 0 | 2,133 |
| 2026-09-12 | 0 | 0 | 1,636 |
| 2026-09-13 | 0 | 0 | 1,626 |
| 2026-09-14 | 0 | 0 | 2,399 |
| 2026-09-15 | 0 | 0 | 1,911 |
| 2026-09-16 | 0 | 0 | 1,728 |
| 2026-09-17 | 0 | 0 | 2,113 |
| 2026-09-18 | 0 | 0 | 2,211 |
| 2026-09-19 | 0 | 0 | 2,240 |
| 2026-09-20 | 0 | 0 | 1,352 |
| 2026-09-21 | 0 | 0 | 0 |
| 2025-09-22 | 0 | 0 | 0 |
| 2025-09-23 | 0 | 0 | 0 |
| 2025-09-24 | 0 | 0 | 0 |
| 2025-09-25 | 0 | 0 | 0 |
| 2025-09-26 | 0 | 0 | 0 |
| 2025-09-27 | 0 | 0 | 0 |
| 2025-09-28 | 0 | 0 | 0 |
| 2025-09-29 | 0 | 0 | 0 |
| 2025-09-30 | 0 | 0 | 0 |
| 2025-10-01 | 0 | 0 | 0 |
| 2025-10-02 | 0 | 0 | 0 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 14B | 45.5% |
| 2 | China | 4.6B | 15% |
| 3 | Japan | 1.4B | 4.5% |
| 4 | Germany | 1.2B | 4.1% |
| 5 | Singapore | 1B | 3.4% |
| 6 | Brazil | 800M | 2.7% |
| 7 | France | 700M | 2.4% |
| 8 | Hong Kong | 600M | 2.1% |
| 9 | Indonesia | 600M | 2% |
| 10 | Spain | 500M | 1.7% |
| 11 | Puerto Rico | 500M | 1.6% |
| 12 | India | 400M | 1.2% |
| 13 | Canada | 300M | 1.1% |
| 14 | Vietnam | 300M | 0.9% |
| 15 | United Kingdom | 200M | 0.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 1 | [space-bunny](https://opencode.ai/data/unknown/space-bunny.md) | - | 57T |
| 2 | [deepseek-v4.1-flash](https://opencode.ai/data/deepseek/deepseek-v4-1-flash.md) | DeepSeek | 33T |
| 3 | [muse-spark-1.3-contributor](https://opencode.ai/data/meta/muse-spark-1-3-contributor.md) | Meta | 31T |
| 4 | [mimo-v2.6-flash](https://opencode.ai/data/xiaomi/mimo-v2-6-flash.md) | Xiaomi | 8.8T |
| 5 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 5.7T |
| 6 | [nemotron-3-ultra](https://opencode.ai/data/nvidia/nemotron-3-ultra.md) | NVIDIA | 3.6T |
| 7 | [longcat-2.5-preview](https://opencode.ai/data/meituan/longcat-2-5-preview.md) | Meituan | 2.6T |
| 8 | [glm-5.3-flash](https://opencode.ai/data/zhipuai/glm-5-3-flash.md) | Zhipu | 2.1T |
| 9 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 794B |
| 10 | [muse-spark-1.2-contributor](https://opencode.ai/data/meta/muse-spark-1-2-contributor.md) | Meta | 738B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| SWE-Bench Verified | 72.8 | resolved | https://www.swebench.com/ |
| SWE-Atlas Codebase QnA | 20.5 | score | https://labs.scale.com/leaderboard/sweatlas-qna |
| SWE-Atlas Refactoring | 24.24 | score | https://labs.scale.com/leaderboard/sweatlas-refactoring |
| SWE-Atlas Test Writing | 28.74 | score | https://labs.scale.com/leaderboard/sweatlas-tw |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.