Short answer
There is no reliable head-to-head evidence here to establish whether Grok Code Fast 1 or GPT-5 is better at coding. There is also a production-status problem: OpenAI marks the gpt-5 API model deprecated, and xAI’s documentation is inconsistent about what the retired grok-code-fast-1 ID serves. xAI’s model page lists it as an alias for grok-build-0.1, while its retirement notice says requests to the old ID redirect to grok-4.3. Verify the model actually served before comparing performance or budgeting. (OpenAI GPT-5 model documentation; xAI model page; xAI retirement notice)
Practical takeaway: Don’t choose between these two names on benchmark results alone. For an existing integration, confirm the resolved model ID. For a new production integration, use an explicitly identified, supported model version. The evidence below provides historical Grok Code Fast 1 results and separate GPT-5 benchmark claims—not a controlled comparison.
What exactly is being compared?
Here, GPT-5 means OpenAI’s API model ID gpt-5, not a later GPT-5 variant or a ChatGPT subscription. OpenAI’s model documentation identifies the snapshot as gpt-5-2025-08-07 and marks GPT-5 deprecated. It lists support for the Responses and Chat Completions endpoints, function calling, and structured outputs. (OpenAI GPT-5 model documentation)
Grok Code Fast 1 is the historical xAI coding-model name. The current xAI model page identifies grok-build-0.1 and lists grok-code-fast-1 as an alias; the retirement notice describes a redirect to grok-4.3 effective May 15, 2026. Because those pages give different mappings, the old name alone is not enough to establish which model a production request uses. (xAI model page; xAI retirement notice)
Coding performance: useful context, not a head-to-head
A third-party 16x Eval article, published August 30, 2025, reports a seven-task, human-rated evaluation of Grok Code Fast 1 using the xAI API. It gives the model an average rating of 7.64, with markedly different results across tasks:
- 9.5/10 on a folder-watcher fix, tying Claude Opus 4 on that task.
- 8/10 on the second attempt at a TypeScript-narrowing task.
- 1/10 on both attempts at a Tailwind CSS v3 z-index task after it missed an invalid class name.
These results describe that article’s tasks, prompts, and rating method. They are not a universal ranking, and the evaluation did not include GPT-5. They also concern the historical Grok Code Fast 1 evaluation, not necessarily whichever model the retired ID serves now. (16x Eval)
16x Eval also reports throughput of roughly 100 tokens per second, but cautions that reasoning tokens before the final answer can delay responses and add cost. That figure is not an end-to-end latency measurement; the article provides no matched GPT-5 latency or agent-run results. (16x Eval)
OpenAI’s August 2025 GPT-5 announcement reports 74.9% on SWE-bench Verified and 88% on Aider polyglot. Those results cannot be compared directly with 16x Eval’s seven-task human ratings: the tests, scoring, and setups differ. They do not establish a Grok Code Fast 1 versus GPT-5 winner. (OpenAI GPT-5 for developers)
Bottom line on quality and speed: The available evidence shows both strong and weak task-specific Grok results, alongside separate GPT-5 benchmark claims. It does not establish which is more accurate, faster in a coding-agent loop, or more reliable on your repository.
API pricing: compare the model actually served
The following are provider-listed API prices in USD per 1 million tokens. GPT-5 is deprecated, so its listed price is not a recommendation to start a new integration. xAI’s Grok figures depend on which model its conflicting documentation says the old Grok ID serves. (OpenAI GPT-5 model documentation; xAI model documentation; xAI pricing)
| Documented model or route | Input | Cached input | Output | Context / pricing condition |
|---|---|---|---|---|
OpenAI gpt-5 |
$1.25 | $0.125 | $10.00 | 400,000-token context; maximum input 272,000 and maximum output 128,000. Model is marked deprecated. |
xAI grok-build-0.1 |
$1.00 | $0.20 | $2.00 | 256,000-token context. xAI’s model page lists grok-code-fast-1 as an alias. |
xAI grok-build-0.1, long-context tier |
$2.00 | $0.40 | $4.00 | Applies when the prompt reaches the listed 200,000-token long-context threshold; xAI says the long-context rates apply to all tokens in that request. |
xAI grok-4.3 |
$1.25 | $0.20 | $2.50 | xAI’s pricing page lists a 1-million-token context and higher rates at the 200,000-token long-context threshold. The retirement notice says the old Grok ID redirects here. |
xAI grok-4.3, long-context tier |
$2.50 | $0.40 | $5.00 | Long-context rates apply to all tokens in the request once the prompt reaches the threshold. |
GPT-5’s rates, context limits, and listed API features come from OpenAI’s model documentation. The Grok Build 0.1 model page provides its short-context rates, context limit, cached-input price, and listed capabilities; xAI’s pricing page specifies the long-context threshold and rates, including Grok 4.3. (OpenAI GPT-5 model documentation; xAI Grok Build 0.1 documentation; xAI pricing)
For budgeting, use the provider-reported token usage and the rates for the model actually served. xAI states that reasoning tokens are billed at the model’s output-token rate. Do not estimate cost from visible final-answer length alone. (xAI pricing documentation)
Production API fit
| Requirement | GPT-5 API | xAI documentation relevant to the old Grok ID |
|---|---|---|
| Status and model identity | gpt-5 is marked deprecated; the page lists the gpt-5-2025-08-07 snapshot. |
The model page lists grok-code-fast-1 as an alias for grok-build-0.1; the retirement notice describes a redirect to grok-4.3. Resolve the discrepancy before relying on the old ID. |
| Context | 400,000 tokens total; maximum input 272,000 and output 128,000. | Grok Build 0.1 lists 256,000 tokens. The old ID’s conflicting mapping means this limit should not be assumed for requests routed to Grok 4.3. |
| Coding-relevant API features | Documentation lists function calling, structured outputs, and streaming. | The Grok Build 0.1 page lists function calling, structured outputs, reasoning, and tool use. Those details describe that model page, not proof of what the retired ID serves. |
| Price predictability for the queried ID | The model page lists rates, but marks GPT-5 deprecated. | The old ID’s conflicting mapping makes its applicable model limits and rates uncertain until xAI confirms the route. |
These are documented model and API details, not results from a production integration test. Verify the model ID and the response’s model information in your own environment before relying on a rate, limit, or feature. (OpenAI GPT-5 model documentation; xAI model documentation; xAI retirement notice)
How to choose for your workload
- For an existing integration: Confirm whether calls reach
gpt-5,grok-build-0.1, orgrok-4.3. An old model label is not enough to compare results or costs. - For a new production system: Prefer explicitly identified, supported model versions over deprecated or redirected IDs.
- For coding quality or agent speed: The available benchmark evidence does not show a winner for your tasks. Run a matched evaluation.
- For API cost: Compare the rates and usage totals for the model actually served, including cached input and billed output tokens where applicable.
A fair, reproducible comparison
Use the same repository snapshot and representative tasks for both models. Include the kinds of work your team actually does—such as bug fixes, refactors, tests, or framework-specific changes. Then:
- Record the exact model ID and version returned for every run.
- Keep prompts, available tools, tool-call limits, and the test environment consistent.
- Score test pass rate and human review against a written rubric; repeat runs where output variability matters.
- Measure time to first token separately from total task time, and record input, cached-input, output, and tool usage.
- Calculate cost from the rates for the model actually served, then assess quality, latency, and cost together.
This is a proposed test method, not a test performed for this article. Until there is a matched evaluation—and xAI clarifies the old Grok ID’s mapping—the defensible conclusion is: no proven coding winner; verify the production model first, then compare it with the exact GPT-5 API version you intend to use.
Sources
GPT-5 model documentation — OpenAI API
Grok Code Fast 1 / Grok Build 0.1 model documentation — xAI
May 15, 2026 model retirement — xAI