GPT-5.2-Codex vs Grok Build 0.1
Both models target agentic coding work, but they come from different labs and different pricing tiers. GPT-5.2-Codex (OpenAI, released 2026-01-14) is built for long, independent engineering sessions with a 400K context window. Grok Build 0.1 (xAI, released 2026-05-20) is a faster, cheaper coding model with a 256K context window. The gap that matters most: input pricing runs 1.75x higher on GPT-5.2-Codex, and Grok Build 0.1 has no public Design Arena scores to weigh against it.
Spec vs spec
| Spec | GPT-5.2-Codex | Grok Build 0.1 |
|---|---|---|
| Context window | 400K | 256K |
| Max output | 128K | — |
| Input modalities | text, image | text, image |
| Output modalities | text | text |
| Released | Jan 14, 2026 | May 20, 2026 |
| Reasoning | always on | always on |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
openai/gpt-5.2-codex
Input · 1M tokens
$1.75 + 3%$1.80
Output · 1M tokens
$14.00 + 3%$14.42
Cache read · 1M tokens
$0.175 + 3%$0.180
FEE — FLAT, EVERY MODEL3%
x-ai/grok-build-0.1
Input · 1M tokens
$1.00 + 3%$1.03
Output · 1M tokens
$2.00 + 3%$2.06
Cache read · 1M tokens
$0.200 + 3%$0.206
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
openai/gpt-5.2-codex
$46.87
$45.50 provider + 3%
x-ai/grok-build-0.1Cheaper
$14.42
$14.00 provider + 3%
Pricing math on a real workload
Run the numbers on 10M input tokens + 2M output tokens, a reasonable stand-in for a day of agentic coding sessions.
- **GPT-5.2-Codex**: provider price is $1.75/M input, $14.00/M output. On OpenKey that's $1.75 × 1.03 = $1.8025/M input and $14.00 × 1.03 = $14.42/M output. Total workload cost: **$45.50**. - **Grok Build 0.1**: provider price is $1.00/M input, $2.00/M output. On OpenKey that's $1.00 × 1.03 = $1.03/M input and $2.00 × 1.03 = $2.06/M output. Total workload cost: **$14.00**.
That's a 3.25x cost difference for the same workload. GPT-5.2-Codex's input tokens alone are priced 1.75x higher than Grok's. If you're running high-volume agent loops, this delta compounds fast.
Coding and agent performance
GPT-5.2-Codex has published Design Arena benchmarks across five agent categories: Android native (elo 1176, rank 15, 47.5% win rate), full-stack (elo 1060, rank 27, 37% win rate), Godot game dev (elo 1187, rank 12, 48% win rate), mobile apps (elo 1172, rank 24, 47.7% win rate), and web apps (elo 1125, rank 22, 40.4% win rate). It's strongest relative to the field in Godot game dev and Android native, weaker in full-stack. Grok Build 0.1 has no Design Arena data available in this comparison, so there's no apples-to-apples benchmark to set against those numbers — you're trading measured performance for lower cost and shorter time-to-market on the model itself (Grok Build 0.1 shipped four months after GPT-5.2-Codex).
Context and long-document work
GPT-5.2-Codex supports a 400K token context window with a 128K max completion limit. Grok Build 0.1 tops out at 256K context with no documented max completion limit in its spec. That's a 1.56x context advantage for GPT-5.2-Codex — relevant if you're feeding it large repos or multi-file diffs in a single call. For most single-PR or single-module coding tasks, 256K is plenty; the gap only bites on whole-codebase context or long agent transcripts that accumulate tool output over many turns.
Parameters and control
Grok Build 0.1 exposes more inference controls: frequency/presence penalty, logprobs, top_logprobs, temperature, top_p, and stop sequences, on top of the shared basics (tools, tool_choice, structured_outputs, response_format, seed, reasoning). GPT-5.2-Codex's parameter list is narrower — reasoning, structured outputs, tool calling, seed — but it does expose reasoning effort levels (low, medium, high, xhigh; default medium), which Grok Build 0.1's spec doesn't document. If you need fine-grained sampling control (penalties, logprobs) for evaluation or fine-tuned agent behavior, Grok Build 0.1 gives you more knobs.
When to pick each
Pick GPT-5.2-Codex for large-context tasks (big repos, long agent traces), for Godot/Android-native agent work where its benchmark ranks are strongest, or when you want adjustable reasoning effort. Pick Grok Build 0.1 for high-volume agentic coding where per-call cost dominates, for tasks needing classic sampling controls (logprobs, penalties), or when 256K context is enough and you'd rather spend the savings on more calls. Both models run on OpenKey under one API key with a flat 3% fee on top of provider list price — no separate accounts or billing setups needed to test both.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume agent loops (cost-sensitive) | Grok Build 0.1 | $14.00 vs $45.50 for a 10M-in/2M-out workload — a 3.25x saving |
| Whole-repo or long-transcript context | GPT-5.2-Codex | 400K context vs 256K, a 1.56x advantage |
| Godot game dev agent tasks | GPT-5.2-Codex | Design Arena rank 12, elo 1187 in that category |
| Android-native agent tasks | GPT-5.2-Codex | Design Arena rank 15, elo 1176, 47.5% win rate |
| Need logprobs or penalty controls | Grok Build 0.1 | Exposes frequency_penalty, presence_penalty, logprobs, top_logprobs — not in GPT-5.2-Codex's parameter list |
| Adjustable reasoning depth per task | GPT-5.2-Codex | Supports four reasoning effort levels (low/medium/high/xhigh); Grok Build 0.1's spec doesn't document effort tiers |
Questions
- How much more expensive is GPT-5.2-Codex than Grok Build 0.1?
- On a 10M-input/2M-output workload, GPT-5.2-Codex costs $45.50 on OpenKey versus $14.00 for Grok Build 0.1 — about 3.25x more. The input price alone is 1.75x higher ($1.8025/M vs $1.03/M on OpenKey after the 3% fee).
- Which model has the bigger context window?
- GPT-5.2-Codex supports 400,000 tokens of context; Grok Build 0.1 supports 256,000. That's a 1.56x ratio in favor of GPT-5.2-Codex, useful for large repos or long agent sessions that accumulate tool output.
- Does Grok Build 0.1 have published coding benchmarks?
- No. This comparison has Design Arena scores for GPT-5.2-Codex across five agent categories (elo 1060–1187, ranks 12–27) but no benchmark data for Grok Build 0.1, so you can't compare them on measured performance here — only on price, context, and parameters.
- Can I use both models with the same API key?
- Yes. OpenKey provides one key across 329 models from 52 labs, including both GPT-5.2-Codex and Grok Build 0.1, with a flat 3% fee added to each provider's list price.