GPT-5.3-Codex vs Grok Build 0.1
Why this pair: Agentic coding models from xAI and OpenAI
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | GPT-5.3-Codex | Grok Build 0.1 |
|---|---|---|
| Developer | Openai | Xai |
| Family | Gpt 5 3 | Grok Build |
| Model | GPT-5.3-Codex | Grok Build 0.1 |
| Version | GPT-5.3-Codex | Grok Build 0.1 |
| Lifecycle | active | preview |
| Released | Unknown | 2026-05-29 |
| Knowledge cutoff | 2025-08-31 | Unknown |
| Input modalities | Unknown | Unknown |
| Output modalities | Unknown | Unknown |
| Context window | 400,000 | 256,000 |
| 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 | Openai (Standard), Openrouter (Standard) | Xai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, structured_outputs, tools |
11 comparable fields · 7 material differences · Interactive comparison only; indexing gate not met
GPT-5.3-Codex Capabilities
Grok Build 0.1 Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
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GPT-5.2OpenAI | vs | GPT-5.3-CodexOpenAI | family variantsimage, text |
GPT-5 NanoOpenAI | vs | GPT-5.3-CodexOpenAI | family variantsimage, text |
GPT-5.3-CodexOpenAI | vs | GPT-5.4 NanoOpenAI | family variantsimage, text |
Grok 4.5xAI | vs | family variantsimage, text | |
Grok 4.3xAI | vs | family variantsimage, text | |
 Gemma 4 31BGoogle DeepMind | vs | GPT-5.3-CodexOpenAI | cross-developer peersimage, text |
Claude Sonnet 4.5Anthropic | vs | GPT-5.3-CodexOpenAI | cross-developer peersimage, text |
Gemma 4 31BGoogle DeepMind | vs | cross-developer peersimage, text | |
Claude Sonnet 4.5Anthropic | vs | cross-developer peersimage, text | |
GPT-5.4 MiniOpenAI | vs | cross-developer peersimage, text | |
GPT-5.4 NanoOpenAI | vs | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
GPT-5.3-Codex vs Grok Build 0.1 FAQs
Is GPT-5.3-Codex or Grok Build 0.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5.3-Codex and Grok Build 0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5.3-Codex or Grok Build 0.1?+
Only GPT-5.3-Codex has a directly sourced input price: $1.75 per million tokens. Only GPT-5.3-Codex has a directly sourced output price: $14.00 per million tokens.
Which has a larger context window, GPT-5.3-Codex or Grok Build 0.1?+
GPT-5.3-Codex has the larger sourced context window. GPT-5.3-Codex supports 400,000 and Grok Build 0.1 supports 256,000.
Which performs better in benchmarks, GPT-5.3-Codex or Grok Build 0.1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can GPT-5.3-Codex or Grok Build 0.1 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-5.3-Codex is not marked open weight; Grok Build 0.1 is not marked open weight.
Can GPT-5.3-Codex and Grok Build 0.1 understand images?+
GPT-5.3-Codex is not documented with image input; Grok Build 0.1 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5.3-Codex or Grok Build 0.1?+
Neither has a larger sourced maximum output. GPT-5.3-Codex is 128,000 and Grok Build 0.1 is —.
Do GPT-5.3-Codex and Grok Build 0.1 support reasoning and tool use?+
GPT-5.3-Codex: reasoning and tool calling. Grok Build 0.1: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5.3-Codex or Grok Build 0.1?+
GPT-5.3-Codex has 2 sourced provider routes; Grok Build 0.1 has 1, so GPT-5.3-Codex has broader tracked availability.
Which offers better value, GPT-5.3-Codex or Grok Build 0.1?+
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.