Gemma 4 E2B vs Qianfan-OCR-Fast
Gemma 4 E2B (2026) and Qianfan-OCR-Fast (2026) are compact production models from Google DeepMind and Baidu AI. Gemma 4 E2B ships a 128k-token context window, while Qianfan-OCR-Fast ships a 66k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qianfan-OCR-Fast is safer overall; choose Gemma 4 E2B when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Gemma 4 E2B | Qianfan-OCR-Fast |
|---|---|---|
| Best for | multimodal apps and tool-calling agents | multimodal apps |
| Decision fit | RAG, Agents, and Long context | Vision |
| Context window | 128k | 66k |
| Cheapest output | - | $2.81/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 4 E2B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemma 4 E2B uniquely exposes Function calling in local model data.
- Local decision data tags Gemma 4 E2B for RAG, Agents, and Long context.
- Qianfan-OCR-Fast uniquely exposes Vision in local model data.
- Local decision data tags Qianfan-OCR-Fast for Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 4 E2B
Unavailable
No complete token price in local provider data
Qianfan-OCR-Fast
$1,247
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 4 E2B and Qianfan-OCR-Fast; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling before moving production traffic.
- Qianfan-OCR-Fast adds Vision in local capability data.
- No overlapping tracked provider route is sourced for Qianfan-OCR-Fast and Gemma 4 E2B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision before moving production traffic.
- Gemma 4 E2B adds Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-31 | 2026-04-20 |
| Context window | 128k | 66k |
| Parameters | 2B | — |
| Architecture | - | decoder only |
| License | Apache 2.0 | Proprietary |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Pricing attribute | Gemma 4 E2B | Qianfan-OCR-Fast |
|---|---|---|
| Input price | - | $0.68/1M tokens |
| Output price | - | $2.81/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 4 E2B | Qianfan-OCR-Fast |
|---|---|---|
| Vision | No | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qianfan-OCR-Fast and function calling: Gemma 4 E2B. Both models share multimodal input, 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 has no token price sourced yet and Qianfan-OCR-Fast has $0.68/1M input tokens. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 4 E2B when long-context analysis and larger context windows are central to the workload. Choose Qianfan-OCR-Fast when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Gemma 4 E2B or Qianfan-OCR-Fast?
Gemma 4 E2B supports 128k tokens, while Qianfan-OCR-Fast supports 66k 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 or Qianfan-OCR-Fast open source?
Gemma 4 E2B is listed under Apache 2.0. Qianfan-OCR-Fast is listed under Proprietary. 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 or Qianfan-OCR-Fast?
Qianfan-OCR-Fast 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 or Qianfan-OCR-Fast?
Both Gemma 4 E2B and Qianfan-OCR-Fast expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, Gemma 4 E2B or Qianfan-OCR-Fast?
Gemma 4 E2B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 4 E2B and Qianfan-OCR-Fast?
Gemma 4 E2B is available on GCP Vertex AI. Qianfan-OCR-Fast is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.