ERNIE X1.1 vs Llama 3.1 405B Instruct
ERNIE X1.1 (2025) and Llama 3.1 405B Instruct (2024) are frontier reasoning models from Baidu AI and AI at Meta. ERNIE X1.1 ships a 64K-token context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, ERNIE X1.1 costs $0.15/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
ERNIE X1.1 is ~1500% cheaper at $0.15/1M; pay for Llama 3.1 405B Instruct only for long-context analysis.
Decision scorecard
Local evidence first| Signal | ERNIE X1.1 | Llama 3.1 405B Instruct |
|---|---|---|
| Decision fit | Agents, Vision, and JSON / Tool use | RAG, Long context, and Classification |
| Context window | 64K | 128K |
| Cheapest output | $0.59/1M tokens | $2.4/1M tokens |
| Provider routes | 1 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- ERNIE X1.1 has the lower cheapest tracked output price at $0.59/1M tokens.
- ERNIE X1.1 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags ERNIE X1.1 for Agents, Vision, and JSON / Tool use.
- Llama 3.1 405B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3.1 405B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
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
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $2,253. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for ERNIE X1.1 and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.1 405B Instruct is $1.81/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- Llama 3.1 405B Instruct adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and ERNIE X1.1; plan for SDK, billing, or endpoint changes.
- ERNIE X1.1 is $1.81/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- ERNIE X1.1 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-09 | 2024-07-23 |
| Context window | 64K | 128K |
| Parameters | — | 405B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | ERNIE X1.1 | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.15/1M tokens | $2.4/1M tokens |
| Output price | $0.59/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | ERNIE X1.1 | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: ERNIE X1.1, multimodal input: ERNIE X1.1, reasoning mode: ERNIE X1.1, function calling: ERNIE X1.1, tool use: ERNIE X1.1, and structured outputs: Llama 3.1 405B Instruct. Both models share the core language-model surface, 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.
For cost, ERNIE X1.1 lists $0.15/1M input and $0.59/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts ERNIE X1.1 lower by about $2.12 per million blended tokens. Availability is 1 providers versus 11, so concentration risk also matters.
Choose ERNIE X1.1 when reasoning depth and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, ERNIE X1.1 or Llama 3.1 405B Instruct?
Llama 3.1 405B Instruct supports 128K 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.
Which is cheaper, ERNIE X1.1 or Llama 3.1 405B Instruct?
ERNIE X1.1 is cheaper on tracked token pricing. ERNIE X1.1 costs $0.15/1M input and $0.59/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is ERNIE X1.1 or Llama 3.1 405B Instruct open source?
ERNIE X1.1 is listed under Proprietary. Llama 3.1 405B Instruct is listed under Open Source. 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 Llama 3.1 405B Instruct?
ERNIE X1.1 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, ERNIE X1.1 or Llama 3.1 405B Instruct?
ERNIE X1.1 has the clearer documented multimodal input signal in this comparison. If multimodal input 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 Llama 3.1 405B Instruct?
ERNIE X1.1 is available on Baidu Qianfan. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.