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xAI: Grok 4.5
xAI
•
Grok 4.5
•
Released 
July 2026

xAI
Grok 4.5

xAI's designated coding and software engineering model — higher quality than Grok 4.3 with a TTFT roughly 5× faster than Grok 4.6.

Modality:
Text
Image
Video
PDF
model ID
x-ai/grok-4.5
Start for free
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Output Speed

49.34
tok/s

Intelligence Index

55.8
/ 100

Context Window

500000
tokens

Input price

12
Anytoken

Output price

36
Anytoken

xAI's Official Coding Model for Agentic Software Engineering

‍

Grok 4.5 is xAI's designated model for software engineering and agentic development workflows. Its official positioning — "intelligent coding model for agentic software, engineering, and workflow tasks" — is backed by training on science, engineering, and math domains and a grok-build-latest API alias that signals its intended role in build tooling. Developers choosing between Grok variants will find Grok 4.5 occupies the space between cost-efficient (Grok 4.3) and frontier quality (Grok 4.6): stronger reasoning than 4.3, faster time-to-first-token than 4.6.

Performance

The Grok 4 Variant Built for Software Engineering Pipelines

xAI explicitly positions Grok 4.5 as an "intelligent coding model for agentic software, engineering, and workflow tasks" — the only Grok 4 variant with a dedicated grok-build-latest API alias. That alias is not cosmetic: it marks Grok 4.5 as the intended stable pointer for developer tooling, IDE integrations, and software build pipelines where consistent engineering-focused behavior matters more than raw frontier capability.

‍

The training set emphasis on science, engineering, and math domains supports this positioning. On independent benchmarks (Artificial Analysis), Grok 4.5 scores 56 on the Intelligence Index (rank #21 of 186), placing it well above the peer median of 35 and materially above Grok 4.3's 38. For multi-step reasoning tasks embedded in code review, architecture analysis, or automated debugging, this gap translates to better handling of complex dependencies.

‍

Grok 4.5 supports reasoning_effort with values "low", "medium", and "high" (default). Unlike Grok 4.3, reasoning cannot be fully disabled — "none" is not an option — and the default is "high", meaning the model applies extended thinking by default. For agentic coding tasks where quality matters more than speed, this default is appropriate. For high-frequency tool calls or classification steps in a larger agent pipeline, explicitly setting reasoning_effort: "low" reduces latency and token cost.

‍

The rate limit profile — 150 requests per second and 50 million tokens per minute (official xAI) — exceeds what most production coding agents require and is significantly higher than Grok 4.3's 37 requests per second. This headroom makes Grok 4.5 practical for multi-agent or multi-user coding environments running concurrent sessions.

‍

Callout: The grok-build-latest alias is the clearest signal in xAI's lineup about intended deployment context. No other Grok 4 model carries a build-specific alias.

Benchmarks

Grok 4.5 Scores 56 on the Intelligence Index — #21 of 186, With a TTFT Advantage Over Its Flagship Sibling

According to Artificial Analysis (independent benchmark provider), Grok 4.5 scores 56 on the Intelligence Index v4.1.1, placing it at rank #21 of 186 models. The benchmark incorporates GPQA Diamond (scientific reasoning), Humanity's Last Exam, SciCode, Terminal-Bench v2.1, and five additional evaluations aligned with engineering and reasoning tasks. This places Grok 4.5 meaningfully above Grok 4.3 (38, #75) and within measurable distance of Grok 4.6 (61, #6). The most practically significant independent finding is the time-to-first-token gap with Grok 4.6: Grok 4.5 measures approximately 8.99 seconds versus Grok 4.6's 42.84 seconds (Artificial Analysis). For an interactive coding tool where the developer waits for the first token of an explanation or code suggestion, a 5× latency difference is directly noticeable. For agentic background pipelines where TTFT is less critical, the advantage narrows.

Output Speed

49.34
tok/s

Intelligence Index

55.8
/ 100

MMLU

Broad world knowledge and problem-solving
0
%

GPQA

PhD-level scientific reasoning across physics, biology, chemistry.
93
%

HLE

Adherence to multi-step structured instructions.
43
%

LiveCodeBench

Tool-calling reliability in long agentic loops.
0
%

Technical Specifications

What the model supports

The reasoning constraint — no "none" option and "high" as default — is the most consequential specification for production deployment. Developers migrating from Grok 4.3, where reasoning can be disabled entirely, will find that every Grok 4.5 request incurs extended thinking. In an agentic coding pipeline with many fast tool-call steps, this adds latency and token cost at each step unless reasoning_effort: "low" is set explicitly. The practical mitigation is to differentiate request types: use "high" for reasoning-heavy steps (architecture review, bug analysis) and "low" for structured tool calls or classification decisions within the same pipeline. The absence of batch API support is the second significant constraint. Offline workloads that process large code corpora asynchronously cannot take advantage of Grok 4.5's quality without real-time API calls, which may conflict with cost or throughput requirements.
Verified Specifications — 
Grok 4.5
Input modalities
Text
Image
Video
PDF
output modalities
Text
Context window
500000
 tokens
Maximum output tokens
500000
Reasoning
Yes
Knowledge cutoff
July 2026
Pricing (standard)
12
 AnyTokens in
 / 
36
 AnyTokens out

Quickstart

Sample code for Grok 4.5

Python
JavaScript
Curl
import requests

url = "https://api.anyapi.ai/v1/chat/completions"

payload = {
    "model": "x-ai/grok-4.5",
    "messages": [
        {
            "role": "user",
            "content": "Hello"
        }
    ]
}
headers = {
    "Authorization": "Bearer anyapi_api_key",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)
import requests url = "https://api.anyapi.ai/v1/chat/completions" payload = { "model": "x-ai/grok-4.5", "messages": [ { "role": "user", "content": "Hello" } ] } headers = { "Authorization": "Bearer anyapi_api_key", "Content-Type": "application/json" } response = requests.post(url, json=payload, headers=headers) print(response.text)
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Code is copied
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer anyapi_api_key', 'Content-Type': 'application/json'},
  body: JSON.stringify({model: 'x-ai/grok-4.5', messages: [{role: 'user', content: 'Hello'}]})
};

fetch('https://api.anyapi.ai/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
const options = { method: 'POST', headers: {Authorization: 'Bearer anyapi_api_key', 'Content-Type': 'application/json'}, body: JSON.stringify({model: 'x-ai/grok-4.5', messages: [{role: 'user', content: 'Hello'}]}) }; fetch('https://api.anyapi.ai/v1/chat/completions', options) .then(res => res.json()) .then(res => console.log(res)) .catch(err => console.error(err));
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Code is copied
curl --request POST \
  --url https://api.anyapi.ai/v1/chat/completions \
  --header 'Authorization: Bearer anyapi_api_key' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "x-ai/grok-4.5",
  "messages": [
    {
      "role": "user",
      "content": "Hello"
    }
  ]
}
'
curl --request POST \ --url https://api.anyapi.ai/v1/chat/completions \ --header 'Authorization: Bearer anyapi_api_key' \ --header 'Content-Type: application/json' \ --data ' { "model": "x-ai/grok-4.5", "messages": [ { "role": "user", "content": "Hello" } ] } '
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Code is copied
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Code examples coming soon...

Comparison

Grok 4.5 vs. Grok 4.6: Coding Specialist or Frontier Flagship?

Choose Grok 4.5 when building interactive coding tools, IDE integrations, or multi-step software engineering agents where the user is waiting for the first response. The ~9s TTFT versus Grok 4.6's ~43s directly affects the feel of the tool. Grok 4.5 also makes sense as the production default for high-volume agentic coding pipelines where the per-task cost advantage and better cache pricing compound at scale.

Dimension
Grok 4.5
Grok 4.6 (high)
Context window
500000
tokens
500000
tokens
Output speed
49.34
tok/s
55.53
tok/s
Intelligence Index
55.8
60.9
Input pricing
12
AnyToken
12
AnyToken
Output pricing
36
AnyToken
36
AnyToken
Knowledge cutoff
July 2026
August 2026

Choose Grok 4.6 when the task demands frontier-level intelligence — complex cross-domain reasoning, research synthesis, or the most difficult debugging scenarios — and interactive latency is not a constraint. The "xhigh" reasoning option is exclusive to Grok 4.6 and represents a qualitative ceiling Grok 4.5 does not reach.

Limitations & Trade-offs

Where Grok 4.5 falls short

1
Grok 4.5 supports reasoning_effort: "low", "medium", and "high" — but unlike Grok 4.3, there is no "none" option and reasoning is always active. The default is "high", meaning every request incurs extended thinking overhead unless explicitly overridden. In agentic pipelines with many lightweight tool-call steps — checking syntax, calling a file reader, formatting output — this overhead adds latency and token cost that Grok 4.3 can avoid entirely. Pipelines with mixed heavy and light reasoning steps need to manage reasoning_effort at the per-call level.
2
At 63.9 tokens per second (Artificial Analysis, independent), Grok 4.5 sits at rank #90 of 186 models — below the measured median of 74.2 t/s. For streaming long code responses to developers who are actively reading output as it generates, this is noticeable. Applications that depend on high streaming throughput — real-time pair programming tools, live code completions — may find faster models in other tiers or providers more suitable.
3
Batch processing is officially not available for Grok 4.5. This eliminates the typical 20–50% cost reduction from async batch inference. For teams processing large code repositories offline — security scanning, documentation generation across thousands of files, mass refactoring review — Grok 4.5 must be called synchronously at full price, which may make the economics unattractive compared to batch-compatible alternatives.
4
Despite being ~5× faster to first token than Grok 4.6, Grok 4.5's ~9-second TTFT is still well above the peer median of 2.84 seconds (Artificial Analysis). For general-purpose chatbots or customer-facing interfaces where sub-second or sub-2-second TTFT is expected, Grok 4.5 is a poor fit. This limitation is specific to its reasoning-first design; the trade-off is deliberate but real.

Best-Fit Workloads

Where this model earns its place

01

Agentic Software Engineering Pipelines

‍

This is xAI's stated purpose for the model. The grok-build-latest alias, the engineering/math training domain focus, and the 150 req/sec rate limit all point toward multi-agent architectures where concurrent coding sessions, CI/CD integrations, or automated PR review pipelines call the model frequently. Setting reasoning_effort: "low" for tool-call coordination steps and "high" for analysis steps allows the agent to optimize latency and cost at different points in the workflow without switching models.

02

Interactive Code Review and Architecture Analysis

‍

The Intelligence Index score of 56 (#21 globally per Artificial Analysis) combined with a TTFT of ~9 seconds makes Grok 4.5 practical for interactive code review tools where a developer submits a file or function and waits for analysis. The model's training on engineering and science domains supports quality output on technical reasoning. Image input allows developers to include architecture diagrams, ERDs, or UI mockups alongside code for context — something a text-only model cannot process. The 9-second TTFT is acceptable for review tasks where depth of output matters more than instant response.

03

Multimodal Technical Documentation with Diagrams

‍

Grok 4.5 accepts image input alongside text — enabling workflows where technical documentation tasks involve screenshots of UIs, architecture diagrams, or network topology charts. Unlike document-to-text pipelines relying solely on text extraction, passing the image directly lets the model reason about visual structure. The 500k context window accommodates large codebases or documentation sets paired with reference images, making it suitable for generating or reviewing technical specifications where visual and textual inputs coexist.

04

Reasoning-Intensive Code Debugging

‍

For debugging tasks that require tracing through non-obvious execution paths, reasoning about state across multiple function calls, or identifying root causes in complex error stacks, Grok 4.5's reasoning depth (default "high") is an asset rather than overhead. The intelligence advantage over Grok 4.3 (56 vs 38) is most visible in tasks requiring multi-step deduction — precisely the kind of work involved in debugging non-trivial software. For simpler syntactic debugging or boilerplate generation, Grok 4.3 at lower cost may suffice.

Pricing in anytokens via AnyAPI
Input
12
₳
Output
36
₳
Cache write
—
₳
Cache read
1.8
₳
Get API access
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PerformanceBenchmarksTechnical SpecificationsQuickstartComparisonLimitations & Trade-offsBest-Fit WorkloadsIntegrationFAQ

Integration

Access Grok 4.5 via AnyAPI.ai

Access Grok 4.5 through AnyAPI.ai using a unified API built for multi-model AI applications. Integrate Grok 4.5 without maintaining a separate provider-specific connection, and keep the flexibility to test, switch, or combine models as your application requirements evolve.

01

One API integration

Access Grok 4.5 and other AI models through the same API workflow instead of maintaining separate integrations for every provider.

02

Easy model switching

Test Grok 4.5 against alternative models or switch models as your performance, capability, or cost requirements change without rebuilding your application around another provider API.

03

Flexible for production

Use Grok 4.5 from experimentation through production while keeping your AI stack flexible as workloads, traffic, and model requirements evolve.

04

Multi-model applications

Use Grok 4.5 for the workloads where it performs best and combine it with other models for tasks that require different capabilities, performance, or efficiency.

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Frequently Asked Questions

Answers to common questions about integrating and using this AI model via AnyAPI.ai

No. Grok 4.5 does not support reasoning_effort: "none" — reasoning is always active. The lowest available setting is "low", which reduces reasoning depth and token usage but cannot be eliminated entirely. If your pipeline requires full reasoning suppression, Grok 4.3 supports "none".

grok-build-latest is an official xAI alias for Grok 4.5 that signals its intended role in software build and development tooling. Using this alias instead of grok-4.5 gives your integration a stable pointer that xAI may update to a newer build-optimized model without requiring a code change on your side. Verify the current target of the alias before using it in production.

Grok 4.5 scores 56 on the Artificial Analysis Intelligence Index versus 61 for Grok 4.6 — a real quality gap. However, Grok 4.5's TTFT of ~9 seconds versus Grok 4.6's ~43 seconds makes it substantially more responsive in interactive coding tools. Per-task cost is also roughly half. For interactive or high-volume agentic use, Grok 4.5 is typically the better choice.

No. Batch API is not supported for Grok 4.5 per official xAI documentation. Workloads requiring async batch processing — offline code analysis, large-scale documentation generation — must use synchronous API calls at standard pricing, which may affect economics for very large jobs.

Yes. Grok 4.5 accepts text and image inputs (JPG/JPEG/PNG, up to 20 MiB per image). This is useful for analyzing UI screenshots, architecture diagrams, or system flow charts alongside code. Output is text only — the model does not generate images.