Qwen2.5-7B-Instruct vs Ling-3.0-tiny
Specs, VRAM requirements and download trends — updated 10 November 2026.
Qwen · A · Open weights
Params
7.6 B
Context
32,768
30d
6.0 M
apache-2.0 · commercial OK
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | Qwen2.5-7B-Instruct | Ling-3.0-tiny |
|---|---|---|
| Deployment | Open weights · also via API | Open weights · also via API |
| Parameters | 7.6 B | 7.9 B |
| Architecture | Qwen2ForCausalLM | BailingMoeV3ForCausalLM |
| Context length | 32,768 | 131,072 |
| Licence | apache-2.0 | mit |
| Commercial use | Allowed | Allowed |
| Languages | 1 | — |
| Downloads 30d | 6,037,480 | 14,221 |
| Downloads all time | 194.0 M | 59 K |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2024-09-16 | 2026-08-10 |
| API input price / 1M tokens | $0.10 | $0.015 |
| API output price / 1M tokens | $0.20 | $0.045 |
| Est. cost per 1M input + 1M output tokens | $0.30 | $0.06 |
| Cached input / 1M tokens | — | $0.003 |
| AA Intelligence Index | — | — |
| AA Coding Index | — | 26.5 |
| AA Agentic Index | — | 4.4 |
| Max output tokens | 29,491 | 250,000 |
| API providers | 1 | 1 |
| Tool calling | Yes | Yes |
| Reasoning mode | No | Yes |
API cost
Estimated cost of 1M input + 1M output tokens via OpenRouter
Qwen2.5-7B-Instruct
$0.30
Ling-3.0-tiny
$0.06
Ling-3.0-tiny is 5.0× cheaper at list price.
Download trend
Daily snapshots, last 90 days (13 Aug – 10 Nov)
12.3 M14 K
Qwen2.5-7B-Instruct
Ling-3.0-tiny
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
Qwen2.5-7B-Instruct · fp16
18.4 GB / 24 GB
Ling-3.0-tiny · fp16 @ 128K ctx
36.8 GB / 24 GB