Compare / Ling 3.0 Tiny vs MiMo-7B-RL
Ling 3.0 Tiny vs MiMo-7B-RL
Updated November 2026
Verdict
Ling 3.0 Tiny scores higher on the Small LM Index: 51.9 vs 40.7. On the 3 benchmarks both labs report, Ling 3.0 Tiny wins 3 and MiMo-7B-RL wins 0. Both need about 6.6 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Ling 3.0 Tiny if…
- you want the strongest model overall
- you need math and reasoning
- you work with long documents
Pick MiMo-7B-RL if…
No clear advantage in the data we have.
Specifications
| Ling 3.0 Tiny | MiMo-7B-RL | |
|---|---|---|
| Small LM Index | 51.9 (likely 47–57) | 40.7 (likely 36–45) |
| Lab | InclusionAI (Ling) · China | Xiaomi (MiMo) · China |
| Released | 2026-08-10 | 2025-04-30 |
| Parameters | 7.9B (1.4B active, MoE) | 7.8B (dense) |
| Memory at 4-bit | ~5.7 GB | ~6.6 GB |
| Context window | 131K tokens | 32K tokens |
| Input | text | text |
| Reasoning | Hybrid (thinking on/off) | Always thinks |
| License | MIT | MIT |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 14.3K | 31.9K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Ling 3.0 Tiny | MiMo-7B-RL |
|---|---|---|
| MMLU-Pro Knowledge | 65.8* | 58.6 |
| GPQA Diamond Knowledge | 73.4 | 54.4 |
| AIME Math | 73.3* | 55.4 |
| LiveCodeBench Coding | ≈ 59 | 49.3 |
| IFBench Instruction following | 60.6* | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Ling 3.0 Tiny or MiMo-7B-RL?
Ling 3.0 Tiny scores higher on the Small LM Index: 51.9 vs 40.7. On the 3 benchmarks both labs report, Ling 3.0 Tiny wins 3 and MiMo-7B-RL wins 0.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 6.6 GB of memory at 4-bit quantization.
Which has the longer context window?
Ling 3.0 Tiny has the longer context window: 131K tokens against 32K.
Can I use Ling 3.0 Tiny and MiMo-7B-RL commercially?
Both are released under the MIT license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.
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