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

Spark-X2.6 4B vs Gemma 4 E2B

Updated November 2026

Verdict

Spark-X2.6 4B scores higher on the Small LM Index: 67.5 vs 31.9. On the 3 benchmarks both labs report, Spark-X2.6 4B wins 3 and Gemma 4 E2B wins 0. Both need about 3.7 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 build agents that call tools
you work with long documents

Pick Gemma 4 E2B if…

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

Specifications

	Spark-X2.6 4B	Gemma 4 E2B
Small LM Index	67.5 (likely 65–70)	31.9 (likely 28–36)
Lab	SparkLLM (XHToken) · China	Google · United States
Released	2026-10-19	2026-04-02
Parameters	4.1B (dense)	5.1B (dense)
Memory at 4-bit	~3.4 GB	~3.7 GB
Context window	1M tokens	128K tokens
Input	text	text, image, audio
Reasoning	Hybrid (thinking on/off)	Hybrid (thinking on/off)
License	Apache-2.0	Apache-2.0
API price / 1M tokens	Self-host only	Self-host only
Hugging Face downloads (30 days)	18.9K	3.3M

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 4 E2B
MMLU-Pro Knowledge	≈ 83	60.0
GPQA Diamond Knowledge	77.1	43.4
Humanity's Last Exam Reasoning	17.9	≈ 3
AIME Math	91.2	37.5
LiveCodeBench Coding	≈ 78	44.0
SWE-bench Verified Coding	62.8	≈ 13
τ²-Bench Agentic	86.9	24.5
IFBench Instruction following	75.8	—
MMMU-Pro Vision	—	44.2
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 4 E2B?

Spark-X2.6 4B scores higher on the Small LM Index: 67.5 vs 31.9. On the 3 benchmarks both labs report, Spark-X2.6 4B wins 3 and Gemma 4 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 3.7 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 128K.

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

Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.