Compare / Spark-X2.5 4B vs Qwen3 4B Thinking 2507
Spark-X2.5 4B vs Qwen3 4B Thinking 2507
Updated November 2026
Verdict
Spark-X2.5 4B scores higher on the Small LM Index: 65.5 vs 55.7. On the 2 benchmarks both labs report, Spark-X2.5 4B wins 2 and Qwen3 4B Thinking 2507 wins 0. Both need about 4.2 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Spark-X2.5 4B if…
- you want the strongest model overall
- you need math and reasoning
- you work with long documents
Pick Qwen3 4B Thinking 2507 if…
- you want the more widely used model (more quantized builds and community support)
Specifications
| Spark-X2.5 4B | Qwen3 4B Thinking 2507 | |
|---|---|---|
| Small LM Index | 65.5 (likely 63–68) | 55.7 (likely 51–60) |
| Lab | SparkLLM (XHToken) · China | Alibaba (Qwen) · China |
| Released | 2026-08-24 | 2025-08-06 |
| Parameters | 4.1B (dense) | 4B (dense) |
| Memory at 4-bit | ~3.4 GB | ~4.2 GB |
| Context window | 1M tokens | 262K tokens |
| Input | text | text |
| Reasoning | Hybrid (thinking on/off) | Always thinks |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 30.3K | 440.9K |
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 | Spark-X2.5 4B | Qwen3 4B Thinking 2507 |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 82 | 74.0 |
| GPQA Diamond Knowledge | 73.7 | 65.8 |
| Humanity's Last Exam Reasoning | 12.3 | ≈ 8 |
| AIME Math | 90.7 | 81.3 |
| LiveCodeBench Coding | ≈ 75 | 55.2 |
| SWE-bench Verified Coding | 41.6 | ≈ 39 |
| τ²-Bench Agentic | 75.1 | — |
| IFBench Instruction following | 75.0 | — |
| IFEval Instruction following | 93.0 | — |
| BFCL Agentic | 65.1 | — |
| HMMT Math | 81.2 | — |
| AA-LCR Long context | 56.3 | — |
| SciCode Coding | 34.7 | — |
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-X2.5 4B or Qwen3 4B Thinking 2507?
Spark-X2.5 4B scores higher on the Small LM Index: 65.5 vs 55.7. On the 2 benchmarks both labs report, Spark-X2.5 4B wins 2 and Qwen3 4B Thinking 2507 wins 0.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 4.2 GB of memory at 4-bit quantization.
Which has the longer context window?
Spark-X2.5 4B has the longer context window: 1M tokens against 262K.
Can I use Spark-X2.5 4B and Qwen3 4B Thinking 2507 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.