ERNIE 5.1 vs GPT-5.3 Codex
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | ERNIE 5.1 | GPT-5.3-Codex |
|---|---|---|
| Developer | Baidu | OpenAI |
| Family | Ernie 5 | Gpt 5 3 |
| Model | ERNIE 5.1 | GPT-5.3-Codex |
| Version | ERNIE 5.1 | GPT-5.3-Codex |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | 2025-08-31 |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 400K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Baidu Qianfan (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | agents, chat, reasoning, search, tools | chat, generation, reasoning, structured_outputs, tools |
13 comparable fields · 8 material differences · Pair passes the primary-source comparison gate
ERNIE 5.1 Capabilities
GPT-5.3 Codex Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
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ERNIE 5.1Baidu | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
ERNIE 5.1Baidu | vs |  DeepSeek-V4-ProDeepSeek | 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 GPT-5.3 Codex FAQs
Is ERNIE 5.1 or GPT-5.3 Codex better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE 5.1 and GPT-5.3 Codex, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, ERNIE 5.1 or GPT-5.3 Codex?+
ERNIE 5.1 is $4.00 and GPT-5.3 Codex is $1.75 per million tokens, so GPT-5.3 Codex is cheaper on this metric. ERNIE 5.1 is $18.00 and GPT-5.3 Codex is $14.00 per million tokens, so GPT-5.3 Codex is cheaper on this metric.
Which has a larger context window, ERNIE 5.1 or GPT-5.3 Codex?+
GPT-5.3 Codex has the larger sourced context window. ERNIE 5.1 supports 131K and GPT-5.3 Codex supports 400K.
Which performs better in benchmarks, ERNIE 5.1 or GPT-5.3 Codex?+
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 GPT-5.3 Codex be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. ERNIE 5.1 is not marked open weight; GPT-5.3 Codex is not marked open weight.
Can ERNIE 5.1 and GPT-5.3 Codex understand images?+
ERNIE 5.1 is not documented with image input; GPT-5.3 Codex is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, ERNIE 5.1 or GPT-5.3 Codex?+
GPT-5.3 Codex has the larger sourced maximum output: ERNIE 5.1 supports 66K and GPT-5.3 Codex supports 128K output tokens.
Do ERNIE 5.1 and GPT-5.3 Codex support reasoning and tool use?+
ERNIE 5.1: reasoning and tool calling. GPT-5.3 Codex: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, ERNIE 5.1 or GPT-5.3 Codex?+
ERNIE 5.1 has 1 sourced provider route; GPT-5.3 Codex has 2, so GPT-5.3 Codex has broader tracked availability.
Which offers better value, ERNIE 5.1 or GPT-5.3 Codex?+
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.