ERNIE X1.1 vs Qwen3.5-4B
ERNIE X1.1 (2025) and Qwen3.5-4B (2026) are frontier reasoning models from Baidu AI and Alibaba. ERNIE X1.1 ships a 64K-token context window, while Qwen3.5-4B ships a 262K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Qwen3.5-4B fits 4x more tokens; pick it for long-context work and ERNIE X1.1 for tighter calls.
Decision scorecard
Local evidence first| Signal | ERNIE X1.1 | Qwen3.5-4B |
|---|---|---|
| Decision fit | Agents, Vision, and JSON / Tool use | Long context and Vision |
| Context window | 64K | 262K |
| Cheapest output | $0.59/1M tokens | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- ERNIE X1.1 has broader tracked provider coverage for fallback and procurement flexibility.
- ERNIE X1.1 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags ERNIE X1.1 for Agents, Vision, and JSON / Tool use.
- Qwen3.5-4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Qwen3.5-4B for Long context and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
ERNIE X1.1
$268
Cheapest tracked route: Baidu Qianfan
Qwen3.5-4B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for ERNIE X1.1 and Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen3.5-4B and ERNIE X1.1; plan for SDK, billing, or endpoint changes.
- ERNIE X1.1 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-09 | 2026-03-02 |
| Context window | 64K | 262K |
| Parameters | — | 4B |
| Architecture | - | - |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | ERNIE X1.1 | Qwen3.5-4B |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.59/1M tokens | - |
| Providers | - |
Capabilities
| Capability | ERNIE X1.1 | Qwen3.5-4B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: ERNIE X1.1, function calling: ERNIE X1.1, and tool use: ERNIE X1.1. Both models share vision and 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: ERNIE X1.1 has $0.15/1M input tokens and Qwen3.5-4B has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose ERNIE X1.1 when reasoning depth and broader provider choice are central to the workload. Choose Qwen3.5-4B when long-context analysis and larger context windows 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, ERNIE X1.1 or Qwen3.5-4B?
Qwen3.5-4B supports 262K tokens, while ERNIE X1.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is ERNIE X1.1 or Qwen3.5-4B open source?
ERNIE X1.1 is listed under Proprietary. Qwen3.5-4B 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, ERNIE X1.1 or Qwen3.5-4B?
Both ERNIE X1.1 and Qwen3.5-4B expose vision. 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 multimodal input, ERNIE X1.1 or Qwen3.5-4B?
Both ERNIE X1.1 and Qwen3.5-4B 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 reasoning mode, ERNIE X1.1 or Qwen3.5-4B?
ERNIE X1.1 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run ERNIE X1.1 and Qwen3.5-4B?
ERNIE X1.1 is available on Baidu Qianfan. Qwen3.5-4B is available on the tracked providers still being sourced. 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: 2026-05-14. Data sourced from public model cards and provider documentation.