# Ling 3.0 Flash Fin Usage, Cost & Rank | OpenCode Data

> Ling 3.0 Flash Fin ranked #16 by tokens across OpenCode last week, with 0.3% of tokens over the past two months. Ling 3.0 Flash Fin costs $0.07 per 1M input tokens and $0.22 per 1M output tokens.

Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution

- Page: https://opencode.ai/data/inclusionai/ling-3-0-flash-fin
- JSON: https://opencode.ai/data/inclusionai/ling-3-0-flash-fin.json
- Model ID: inclusionai/ling-3.0-flash-fin
- Lab: inclusionAI
- Updated: 2026-10-02T07:36:56.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 262K |
| Max output | 33K |
| Knowledge cutoff | - |
| Release date | 2026-08-27 |
| Input modalities | text |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | No |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.07 | $0.22 | $0.01 | - |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #16 |
| Tokens | 2.4T |
| Share of all tokens | 0.3% |
| Change vs previous 2 months | +100% |
| Unique users | 129K |
| Completed sessions | 3,492,963 |
| Average tokens per session | 690K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 89.4% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-28 | 20B | 2.3K | 14,780 |
| 2026-08-29 | 56B | 4.1K | 38,030 |
| 2026-08-30 | 59B | 6.1K | 52,402 |
| 2026-08-31 | 59B | 6.7K | 64,633 |
| 2026-09-01 | 59B | 6K | 61,682 |
| 2026-09-02 | 58B | 5.5K | 57,502 |
| 2026-09-03 | 58B | 5.5K | 56,607 |
| 2026-09-04 | 60B | 5K | 50,587 |
| 2026-09-05 | 61B | 4.6K | 51,477 |
| 2026-09-06 | 60B | 4.5K | 64,421 |
| 2026-09-07 | 60B | 4.4K | 89,226 |
| 2026-09-08 | 61B | 4.1K | 81,572 |
| 2026-09-09 | 60B | 3.8K | 214,552 |
| 2026-09-10 | 59B | 3.6K | 168,347 |
| 2026-09-11 | 52B | 3.5K | 200,347 |
| 2026-09-12 | 57B | 3K | 95,100 |
| 2026-09-13 | 57B | 3.3K | 122,037 |
| 2026-09-14 | 85B | 3.9K | 118,906 |
| 2026-09-15 | 95B | 3.8K | 108,666 |
| 2026-09-16 | 96B | 3.9K | 133,547 |
| 2026-09-17 | 98B | 2.8K | 345,874 |
| 2026-09-18 | 98B | 3.2K | 198,572 |
| 2026-09-19 | 94B | 3.6K | 112,895 |
| 2026-09-20 | 101B | 3.1K | 125,583 |
| 2026-09-21 | 109B | 2.7K | 93,696 |
| 2026-09-22 | 110B | 2.9K | 81,682 |
| 2026-09-23 | 112B | 2.9K | 87,766 |
| 2026-09-24 | 103B | 2.8K | 76,793 |
| 2026-09-25 | 99B | 2.7K | 84,215 |
| 2026-09-26 | 96B | 2.4K | 91,439 |
| 2026-09-27 | 88B | 2.4K | 89,342 |
| 2026-09-28 | 72B | 2.7K | 91,167 |
| 2026-09-29 | 0 | 2.6K | 55,585 |
| 2026-09-30 | 0 | 2.1K | 47,822 |
| 2026-10-01 | 0 | 2K | 49,776 |
| 2026-10-02 | 0 | 512 | 16,335 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | China | 396B | 16.4% |
| 2 | India | 224B | 9.3% |
| 3 | United States | 184B | 7.6% |
| 4 | Brazil | 127B | 5.2% |
| 5 | Indonesia | 108B | 4.5% |
| 6 | Germany | 85B | 3.5% |
| 7 | Pakistan | 56B | 2.3% |
| 8 | Netherlands | 50B | 2.1% |
| 9 | France | 45B | 1.9% |
| 10 | Türkiye | 44B | 1.8% |
| 11 | Egypt | 44B | 1.8% |
| 12 | Spain | 41B | 1.7% |
| 13 | Vietnam | 36B | 1.5% |
| 14 | Argentina | 35B | 1.5% |
| 15 | Singapore | 34B | 1.4% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 12 | [gpt-6-luna](https://opencode.ai/data/openai/gpt-6-luna.md) | OpenAI | 638B |
| 13 | [deepseek-v4-pro](https://opencode.ai/data/deepseek/deepseek-v4-pro.md) | DeepSeek | 462B |
| 14 | [mimo-v2.6-pro](https://opencode.ai/data/xiaomi/mimo-v2-6-pro.md) | Xiaomi | 461B |
| 15 | [nemotron-3.5-lightning](https://opencode.ai/data/nvidia/nemotron-3-5-lightning.md) | NVIDIA | 264B |
| 16 | [ling-3.0-flash-fin](https://opencode.ai/data/inclusionai/ling-3-0-flash-fin.md) | inclusionAI | 256B |
| 17 | [qwen3.8-flash](https://opencode.ai/data/alibaba/qwen3-8-flash.md) | Qwen | 254B |
| 18 | [gpt-5.6-luna](https://opencode.ai/data/openai/gpt-5-6-luna.md) | OpenAI | 194B |
| 19 | [minimax-m3](https://opencode.ai/data/minimax/minimax-m3.md) | MiniMax | 180B |
| 20 | [mai-experimental-test](https://opencode.ai/data/unknown/mai-experimental-test.md) | - | 171B |
| 21 | [kimi-k2.7-code](https://opencode.ai/data/moonshotai/kimi-k2-7-code.md) | Moonshot | 135B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| FinFIRST | 52.85 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| FinSearchComp Verified | 77.04 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| FinCRAFT | 51.74 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| Finance Agent | 69.19 | strict-pass | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| Finance Agent | 59.81 | strict-pass | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| APEX-Agents | 29.17 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| SpreadsheetBench | 86.5 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| SpreadsheetBench | 21.81 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |
| tau3-bench | 41 | score | https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin |

## 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.