ERNIE 4.5 0.3B PT vs Qwen3.8 Flash
At a Glance
| Compare | ERNIE 4.5 0.3B PTBaidu | Qwen3.8 FlashQwen |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #4 of 44$0.021 per LiveBench case |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.113Deepinfra ↗ · Sep 21, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.382Deepinfra ↗ · Sep 21, 2026 |
| Context windowMaximum documented tokens | 131K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 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-4.5-0.3B-PT | Qwen3.8-Flash |
|---|---|---|
| Developer | Baidu | Qwen |
| Family | Ernie 4 5 0 3b Pt | Qwen3 8 Flash |
| Model | ERNIE-4.5-0.3B-PT | Qwen3.8-Flash |
| Version | ERNIE-4.5-0.3B-PT | Qwen3.8-Flash |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 131K | 1,000K |
| Total parameters | 360.7M | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation | agents, chat, computer-use, reasoning, structured_outputs, tools, vision |
ERNIE 4.5 0.3B PT Capabilities
Qwen3.8 Flash Capabilities
Primary Evidence
Sources and Freshness
Questions
ERNIE 4.5 0.3B PT vs Qwen3.8 Flash FAQs
Is ERNIE 4.5 0.3B PT or Qwen3.8 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE 4.5 0.3B PT and Qwen3.8 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
Only Qwen3.8 Flash has a directly sourced input price: $0.113 per million tokens. Only Qwen3.8 Flash has a directly sourced output price: $0.382 per million tokens.
Which has a larger context window, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
Qwen3.8 Flash has the larger sourced context window. ERNIE 4.5 0.3B PT supports 131K and Qwen3.8 Flash supports 1,000K.
Which performs better in benchmarks, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can ERNIE 4.5 0.3B PT or Qwen3.8 Flash be self-hosted?+
ERNIE 4.5 0.3B PT is the only model in this pair currently marked as self-hostable. ERNIE 4.5 0.3B PT is open weight; Qwen3.8 Flash is not marked open weight.
Can ERNIE 4.5 0.3B PT and Qwen3.8 Flash understand images?+
ERNIE 4.5 0.3B PT is not documented with image input; Qwen3.8 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
Neither has a larger sourced maximum output. ERNIE 4.5 0.3B PT is — and Qwen3.8 Flash is 131K.
Do ERNIE 4.5 0.3B PT and Qwen3.8 Flash support reasoning and tool use?+
ERNIE 4.5 0.3B PT: none of these features are definitively sourced. Qwen3.8 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
ERNIE 4.5 0.3B PT has 0 sourced provider routes; Qwen3.8 Flash has 4, so Qwen3.8 Flash has broader tracked availability.
Which offers better value, ERNIE 4.5 0.3B PT or Qwen3.8 Flash?+
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.