LLM Reference

Gemma 4 E2B IT vs Qwen3.5-9B

Gemma 4 E2B IT (2026) and Qwen3.5-9B (2026) are compact production models from Google DeepMind and Alibaba. Gemma 4 E2B IT ships a 128k-token context window, while Qwen3.5-9B ships a 262k-token context window. On MMLU PRO, Qwen3.5-9B leads by 22.5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Gemma 4 E2B IT is safer overall; choose Qwen3.5-9B when long-context analysis matters.

Decision scorecard

Local evidence first
SignalGemma 4 E2B ITQwen3.5-9B
Best formultimodal apps, tool-calling agents, and provider-routed productionmultimodal apps, tool-calling agents, and provider-routed production
Decision fitRAG, Agents, and Long contextRAG, Agents, and Long context
Context window128k262k
Cheapest output-$0.15/1M tokens
Provider routes2 tracked3 tracked
Shared benchmarks2 rowsMMLU PRO leader

Decision tradeoffs

Choose Gemma 4 E2B IT when...
  • Local decision data tags Gemma 4 E2B IT for RAG, Agents, and Long context.
Choose Qwen3.5-9B when...
  • Qwen3.5-9B leads the largest shared benchmark signal on MMLU PRO by 22.5 points.
  • Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.5-9B uniquely exposes Vision and Tool use in local model data.
  • Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Gemma 4 E2B IT

Unavailable

No complete token price in local provider data

Qwen3.5-9B

$118

Cheapest tracked route/tier: Together AI

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Gemma 4 E2B IT -> Qwen3.5-9B
  • No overlapping tracked provider route is sourced for Gemma 4 E2B IT and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-9B adds Vision and Tool use in local capability data.
Qwen3.5-9B -> Gemma 4 E2B IT
  • No overlapping tracked provider route is sourced for Qwen3.5-9B and Gemma 4 E2B IT; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision and Tool use before moving production traffic.

Specs

Specification
Released2026-03-312026-03-02
Context window128k262k
Parameters2B9B
Architecture-decoder only
LicenseApache 2.0Apache 2.0
Knowledge cutoff2025-01-

Pricing and availability

Pricing attributeGemma 4 E2B ITQwen3.5-9B
Input price-$0.10/1M tokens
Output price-$0.15/1M tokens
Providers

Capabilities

CapabilityGemma 4 E2B ITQwen3.5-9B
VisionNoYes
MultimodalYesYes
ReasoningNoNo
Function callingYesYes
Tool useNoYes
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGemma 4 E2B ITQwen3.5-9B
MMLU PRO60.082.5
Google-Proof Q&A43.481.7

Deep dive

On shared benchmark coverage, MMLU PRO has Gemma 4 E2B IT at 60 and Qwen3.5-9B at 82.5, with Qwen3.5-9B ahead by 22.5 points; Google-Proof Q&A has Gemma 4 E2B IT at 43.4 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 38.3 points. The largest visible gap is 38.3 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on vision: Qwen3.5-9B and tool use: Qwen3.5-9B. Both models share multimodal input, function calling, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Gemma 4 E2B IT has no token price sourced yet and Qwen3.5-9B has $0.10/1M input tokens. Provider availability is 2 tracked routes versus 3. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemma 4 E2B IT when provider fit are central to the workload. Choose Qwen3.5-9B when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, Gemma 4 E2B IT or Qwen3.5-9B?

Qwen3.5-9B supports 262k tokens, while Gemma 4 E2B IT supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemma 4 E2B IT or Qwen3.5-9B open source?

Gemma 4 E2B IT is listed under Apache 2.0. Qwen3.5-9B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Gemma 4 E2B IT or Qwen3.5-9B?

Qwen3.5-9B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Gemma 4 E2B IT or Qwen3.5-9B?

Both Gemma 4 E2B IT and Qwen3.5-9B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for function calling, Gemma 4 E2B IT or Qwen3.5-9B?

Both Gemma 4 E2B IT and Qwen3.5-9B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Gemma 4 E2B IT and Qwen3.5-9B?

Gemma 4 E2B IT is available on Google AI Studio and GCP Vertex AI. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.