# coding-glm-5.3 Usage, Cost & Rank | OpenCode Data

> coding-glm-5.3 ranked #45 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/zhipu/coding-glm-5-3
- JSON: https://opencode.ai/data/zhipu/coding-glm-5-3.json
- Model ID: coding-glm-5.3
- Lab: Zhipu
- Updated: 2026-10-03T23:42:55.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #45 |
| Tokens | 1.8M |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 1 |
| Completed sessions | 1 |
| Average tokens per session | 1.8M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 69.9% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-03 | 1.8M | 1 | 1 |
| 2026-10-04 | 0 | 0 | 0 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 0 | 100% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 40 | [test-novita-dsf4.1](https://opencode.ai/data/deepseek/test-novita-dsf4-1.md) | DeepSeek | 497M |
| 41 | [qwen3.6-plus](https://opencode.ai/data/alibaba/qwen3-6-plus.md) | Qwen | 343M |
| 42 | [minimax-m2.5](https://opencode.ai/data/minimax/minimax-m2-5.md) | MiniMax | 332M |
| 43 | [gpt-5-nano](https://opencode.ai/data/openai/gpt-5-nano.md) | OpenAI | 253M |
| 44 | [qwen3.7-max](https://opencode.ai/data/alibaba/qwen3-7-max.md) | Qwen | 245M |
| 45 | [coding-glm-5.3](https://opencode.ai/data/zhipu/coding-glm-5-3.md) | Zhipu | 1.8M |
| 46 | [exo](https://opencode.ai/data/unknown/exo.md) | - | 533K |
| 47 | [qwen3.8-27b](https://opencode.ai/data/alibaba/qwen3-8-27b.md) | Qwen | 62K |
| 48 | [test-novita-kimi k3](https://opencode.ai/data/moonshot/test-novita-kimi-k3.md) | Moonshot | 24K |
| 49 | [test-novita-openai](https://opencode.ai/data/openai/test-novita-openai.md) | OpenAI | 451 |

## 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.