ERNIE 5.1 vs Bonsai 8B
At a Glance
| Compare |  ERNIE 5.1Baidu |  Bonsai 8BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 131K | 66K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 18, 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 | Bonsai 8B |
|---|---|---|
| Developer | Baidu | PrismML |
| Family | Ernie 5 | Bonsai 8b |
| Model | ERNIE 5.1 | Bonsai 8B |
| Version | ERNIE 5.1 | Bonsai 8B |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 131K | 66K |
| Total parameters | Unknown | 8.2B |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | No |
| Self-hostable | No | Yes |
| Provider access | Baidu Qianfan (Standard) | Unknown |
| Capabilities | agents, chat, reasoning, search, tools | chat, generation |
| Effective bit width | Unknown | 1 bit per weight |
| Weight size | Unknown | 1.16 GB |
| Weight format | Unknown | Binary Q1_0 |
ERNIE 5.1 Capabilities
Bonsai 8B Capabilities
Related Comparisons
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|---|---|---|---|
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ERNIE 5.1Baidu | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peerstext |
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 Bonsai 8B FAQs
Is ERNIE 5.1 or Bonsai 8B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE 5.1 and Bonsai 8B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, ERNIE 5.1 or Bonsai 8B?+
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 Bonsai 8B?+
ERNIE 5.1 has the larger sourced context window. ERNIE 5.1 supports 131K and Bonsai 8B supports 66K.
Which performs better in benchmarks, ERNIE 5.1 or Bonsai 8B?+
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 Bonsai 8B be self-hosted?+
Bonsai 8B is the only model in this pair currently marked as self-hostable. ERNIE 5.1 is not marked open weight; Bonsai 8B is open weight.
Can ERNIE 5.1 and Bonsai 8B understand images?+
ERNIE 5.1 is not documented with image input; Bonsai 8B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, ERNIE 5.1 or Bonsai 8B?+
Neither has a larger sourced maximum output. ERNIE 5.1 is 66K and Bonsai 8B is —.
Do ERNIE 5.1 and Bonsai 8B support reasoning and tool use?+
ERNIE 5.1: reasoning and tool calling. Bonsai 8B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, ERNIE 5.1 or Bonsai 8B?+
ERNIE 5.1 has 1 sourced provider route; Bonsai 8B has 0, so ERNIE 5.1 has broader tracked availability.
Which offers better value, ERNIE 5.1 or Bonsai 8B?+
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.