Compare / Ling 3.0 Tiny vs Gemma 4 E4B

Ling 3.0 Tiny vs Gemma 4 E4B

Updated November 2026

Verdict

Ling 3.0 Tiny scores higher on the Small LM Index: 51.9 vs 38.2. On the 3 benchmarks both labs report, Ling 3.0 Tiny wins 2 and Gemma 4 E4B wins 1. Both need about 5.7 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 Gemma 4 E4B if…

you need image input
you want the more widely used model (more quantized builds and community support)

Specifications

	Ling 3.0 Tiny	Gemma 4 E4B
Small LM Index	51.9 (likely 47–57)	38.2 (likely 34–42)
Lab	InclusionAI (Ling) · China	Google · United States
Released	2026-08-10	2026-04-02
Parameters	7.9B (1.4B active, MoE)	8B (dense)
Memory at 4-bit	~5.7 GB	~5.6 GB
Context window	131K tokens	128K tokens
Input	text	text, image, audio
Reasoning	Hybrid (thinking on/off)	Hybrid (thinking on/off)
License	MIT	Apache-2.0
API price / 1M tokens	Self-host only	Self-host only
Hugging Face downloads (30 days)	14.3K	4.1M

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	Gemma 4 E4B
MMLU-Pro Knowledge	65.8^*	69.4
GPQA Diamond Knowledge	73.4	58.6
AIME Math	73.3^*	42.5
LiveCodeBench Coding	≈ 59	52.0
τ²-Bench Agentic	—	42.2
IFBench Instruction following	60.6^*	—
MMMU-Pro Vision	—	52.6

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 Gemma 4 E4B?

Ling 3.0 Tiny scores higher on the Small LM Index: 51.9 vs 38.2. On the 3 benchmarks both labs report, Ling 3.0 Tiny wins 2 and Gemma 4 E4B wins 1.

Which is cheaper to run?

Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 5.7 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 128K.

Can I use Ling 3.0 Tiny and Gemma 4 E4B commercially?

Ling 3.0 Tiny is released under MIT and Gemma 4 E4B under Apache-2.0. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.