# flint-40b Usage, Cost & Rank | OpenCode Data

> flint-40b ranked #36 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/recursive/flint-40b
- JSON: https://opencode.ai/data/recursive/flint-40b.json
- Model ID: flint-40b
- Lab: Recursive
- Updated: 2026-10-22T11:53:58.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #36 |
| Tokens | 13B |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 3.4K |
| Completed sessions | 37,185 |
| Average tokens per session | 355K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 81.4% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-21 | 2.8B | 942 | 9,191 |
| 2026-10-22 | 10B | 2.5K | 27,994 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 1.4B | 10.6% |
| 2 | China | 1.3B | 10% |
| 3 | India | 1B | 7.4% |
| 4 | Indonesia | 700M | 5% |
| 5 | Brazil | 600M | 4.7% |
| 6 | Russia | 500M | 4% |
| 7 | Germany | 500M | 3.6% |
| 8 | Spain | 400M | 2.7% |
| 9 | Mexico | 300M | 2.2% |
| 10 | Philippines | 300M | 2.2% |
| 11 | Vietnam | 300M | 2% |
| 12 | United Kingdom | 300M | 1.9% |
| 13 | Argentina | 200M | 1.8% |
| 14 | Australia | 200M | 1.8% |
| 15 | France | 200M | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 32 | [mimo-v2.5-pro](https://opencode.ai/data/xiaomi/mimo-v2-5-pro.md) | Xiaomi | 21B |
| 33 | [longcat-2.0](https://opencode.ai/data/meituan/longcat-2-0.md) | Meituan | 20B |
| 34 | [qwen3.8-max](https://opencode.ai/data/alibaba/qwen3-8-max.md) | Qwen | 14B |
| 35 | [hy4-preview](https://opencode.ai/data/tencent/hy4-preview.md) | Tencent | 14B |
| 36 | [flint-40b](https://opencode.ai/data/recursive/flint-40b.md) | Recursive | 13B |
| 37 | [hy3](https://opencode.ai/data/tencent/hy3.md) | Tencent | 12B |
| 38 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 11B |
| 39 | [omen-alpha](https://opencode.ai/data/unknown/omen-alpha.md) | - | 10B |
| 40 | [grok-4.7](https://opencode.ai/data/xai/grok-4-7.md) | xAI | 9.4B |
| 41 | [kimi-k2.6](https://opencode.ai/data/moonshotai/kimi-k2-6.md) | Moonshot | 2.8B |

## 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.