Compare / Spark-X2.6 4B vs Gemma 3n E2B

Spark-X2.6 4B vs Gemma 3n E2B

Updated November 2026

Verdict

Spark-X2.6 4B scores higher on the Small LM Index: 67.5 vs 14.3. On the 2 benchmarks both labs report, Spark-X2.6 4B wins 2 and Gemma 3n E2B wins 0. Both need about 4 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.

Pick Spark-X2.6 4B if…

you want the strongest model overall
you need math and reasoning
you work with long documents
you need a permissive license (Apache-2.0)

Pick Gemma 3n E2B if…

you need image input

Specifications

	Spark-X2.6 4B	Gemma 3n E2B
Small LM Index	67.5 (likely 65–70)	14.3 (likely 12–17)
Lab	SparkLLM (XHToken) · China	Google · United States
Released	2026-10-19	2025-06-26
Parameters	4.1B (dense)	5.4B (dense)
Memory at 4-bit	~3.4 GB	~4 GB
Context window	1M tokens	32K tokens
Input	text	text, image, audio, video
Reasoning	Hybrid (thinking on/off)	No thinking
License	Apache-2.0	Gemma
API price / 1M tokens	Self-host only	Self-host only
Hugging Face downloads (30 days)	18.9K	38.3K

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	Spark-X2.6 4B	Gemma 3n E2B
MMLU-Pro Knowledge	≈ 83	40.5
GPQA Diamond Knowledge	77.1	24.8
Humanity's Last Exam Reasoning	17.9	≈ 1
AIME Math	91.2	6.7
LiveCodeBench Coding	≈ 78	18.6
SWE-bench Verified Coding	62.8	≈ 3
τ²-Bench Agentic	86.9	—
IFBench Instruction following	75.8	—
MMLU Knowledge	—	60.1
Multilingual MMLU Multilingual	—	55.1
IFEval Instruction following	93.6	—
BFCL Agentic	71.8	—
HMMT Math	81.3	—
AA-LCR Long context	67.3	—
SciCode Coding	36.8	—

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, Spark-X2.6 4B or Gemma 3n E2B?

Spark-X2.6 4B scores higher on the Small LM Index: 67.5 vs 14.3. On the 2 benchmarks both labs report, Spark-X2.6 4B wins 2 and Gemma 3n E2B wins 0.

Which is cheaper to run?

Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 4 GB of memory at 4-bit quantization.

Which has the longer context window?

Spark-X2.6 4B has the longer context window: 1M tokens against 32K.

Can I use Spark-X2.6 4B and Gemma 3n E2B commercially?

Spark-X2.6 4B is released under Apache-2.0 and Gemma 3n E2B under Gemma. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.