ERNIE 5.1 vs Llama 3.1 405B Instruct
At a Glance
| Compare |  ERNIE 5.1Baidu | |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 131K | 131K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | ERNIE 5.1 | Llama-3.1-405B-Instruct |
|---|---|---|
| Developer | Baidu | Meta |
| Family | Ernie 5 | Llama 3 1 405b Instruct |
| Model | ERNIE 5.1 | Llama-3.1-405B-Instruct |
| Version | ERNIE 5.1 | Llama-3.1-405B-Instruct |
| Lifecycle | active | active |
| Released | Unknown | 2024-07-23 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 131K | 131K |
| Total parameters | Unknown | 405.9B |
| Active parameters | Unknown | Unknown |
| License | Unknown | llama3.1 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Baidu Qianfan (Standard) | Together Ai (Standard) |
| Capabilities | agents, chat, reasoning, search, tools | chat, generation, tools |
ERNIE 5.1 Capabilities
Llama 3.1 405B Instruct Capabilities
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|---|---|---|---|
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ERNIE 5.1Baidu | vs | Grok 4.6xAI | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | ERNIE 5.1Baidu | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  GLM-5.3Z.ai | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  Hy4 previewTencent | cross-developer peerstext |
ERNIE 5.1Baidu | vs | Seed 2.1 ProByteDance Seed | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
ERNIE 5.1 vs Llama 3.1 405B Instruct FAQs
Is ERNIE 5.1 or Llama 3.1 405B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE 5.1 and Llama 3.1 405B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, ERNIE 5.1 or Llama 3.1 405B Instruct?+
Only ERNIE 5.1 has a directly sourced input price: $4.00 per million tokens. Only ERNIE 5.1 has a directly sourced output price: $18.00 per million tokens.
Which has a larger context window, ERNIE 5.1 or Llama 3.1 405B Instruct?+
Neither model has a larger sourced context window in this comparison. ERNIE 5.1 is 131K and Llama 3.1 405B Instruct is 131K.
Which performs better in benchmarks, ERNIE 5.1 or Llama 3.1 405B Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can ERNIE 5.1 or Llama 3.1 405B Instruct be self-hosted?+
Llama 3.1 405B Instruct is the only model in this pair currently marked as self-hostable. ERNIE 5.1 is not marked open weight; Llama 3.1 405B Instruct is open weight.
Can ERNIE 5.1 and Llama 3.1 405B Instruct understand images?+
ERNIE 5.1 is not documented with image input; Llama 3.1 405B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, ERNIE 5.1 or Llama 3.1 405B Instruct?+
Neither has a larger sourced maximum output. ERNIE 5.1 is 66K and Llama 3.1 405B Instruct is —.
Do ERNIE 5.1 and Llama 3.1 405B Instruct support reasoning and tool use?+
ERNIE 5.1: reasoning and tool calling. Llama 3.1 405B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, ERNIE 5.1 or Llama 3.1 405B Instruct?+
ERNIE 5.1 has 1 sourced provider route; Llama 3.1 405B Instruct has 1, a tie.
Which offers better value, ERNIE 5.1 or Llama 3.1 405B Instruct?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.