Gemma 4 (Google) vs StepFun Step 3.5 Flash

Which one should you pick? Here's the full breakdown.

Our Pick

Gemma 4 (Google)

A
8.3/10

Google DeepMind's open-weights model family -- multimodal, 256K context, runs on edge devices

StepFun Step 3.5 Flash

B
7.8/10

StepFun's (China) agent-focused open-weight model -- Step 3.5 Flash launched 2026-02-01. 196B sparse MoE, ~11B active. Benchmarks slightly ahead of DeepSeek V3.2 at over 3x smaller total size. Step 3 (321B / 38B active, Apache 2.0) and Step3-VL-10B multimodal also in the family

CategoryGemma 4 (Google)StepFun Step 3.5 Flash
Ease of Use7.06.0
Output Quality8.08.0
Value10.09.0
Features8.08.0
Overall8.37.8

Pricing Comparison

FeatureGemma 4 (Google)StepFun Step 3.5 Flash
Free TierYesYes
Starting Price$0$0

Benchmark Head-to-Head

Gemma 4 31B benchmarks — StepFun Step 3.5 Flash has no published benchmarks

BenchmarkScore
MMLU83%
GPQA Diamond84.3%
AIME 202689.2%
HumanEval85%

Which Should You Pick?

Pick Gemma 4 (Google) if...

  • Easier to use (7 vs 6)
  • Better value for money (10/10)

Developers and businesses who need a permissively licensed multimodal LLM they can self-host or fine-tune. Especially good for multilingual use cases and on-device deployment.

Visit Gemma 4 (Google)

Pick StepFun Step 3.5 Flash if...

Teams building agent systems on Chinese open-weight foundations who want something other than DeepSeek or Qwen, especially if agentic tool-use is the primary workload. Also good for Chinese-market products where StepFun's domestic tuning advantages matter. And for anyone looking to add diversity to their open-weight evaluation matrix beyond the top-3 Chinese labs.

Visit StepFun Step 3.5 Flash

Our Verdict

Gemma 4 (Google) edges out StepFun Step 3.5 Flash with a 8.3 vs 7.8 overall score. Both are solid picks, but Gemma 4 (Google) has the advantage in value.