Head-to-Head Model Comparison

Grok 4.5 vs Grok 4.3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Grok 4.5 vs Grok 4.3: Benchmarks, Pricing & Speed Comparison

Grok 4.5 by xAI and Grok 4.3 by xAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Grok 4.3 holds a notable pricing advantage for token ingestion. On output generation, Grok 4.3 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok 4.3 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Grok 4.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

Head-to-Head Comparison

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xAI

Grok 4.5

Fast Reasoning

High-throughput, budget-friendly generalist combining fast hybrid reasoning with reduced API pricing of $2/$6 per million tokens.

Intelligence Index75 / 100
Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

500K tokens

SWE-bench Verified:

74.2%

xAI

Grok 4.3

Default Grok

xAI's standard balanced general-purpose model combining 1M context, robust agentic tool support, and lower hallucination rates.

Intelligence Index71 / 100
Input Token:

$1.25 / 1M

Output Token:

$2.50 / 1M

Context Window:

1M tokens

SWE-bench Verified:

71.4%

Key Differences at a Glance

  • Grok 4.3 is 2.0x cheaper for API usage (input + output tokens combined).
  • Grok 4.3 has a larger context window (1M vs 500K tokens).
  • Grok 4.5 is faster at 130 tok/s vs 110 tok/s.
  • Grok 4.5 leads on SWE-bench coding (74.2% vs 71.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 4.5Grok 4.3
Intelligence Index
Composite reasoning & knowledge score (0-100)
7571
Provider
xAIxAI
Input Price
Cost per million input tokens
$2.00 / 1M$1.25 / 1M
Output Price
Cost per million output tokens
$6.00 / 1M$2.50 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.35 / 1M$0.72 / 1M
Context Window
Maximum input + output tokens
500K tokens~750 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K66K
Throughput Speed
Tokens generated per second
130 tok/s110 tok/s
SWE-bench Verified
Real-world software engineering
74.2%71.4%
GPQA Diamond
Graduate-level reasoning
75.9%73.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.31 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Grok 4.5
+2.8% SWE-bench lead
Cost
Grok 4.3
2.0x cheaper monthly runtime
Speed
Grok 4.5
+18% faster generation
Context
Grok 4.3
1M tokens window

Empirical Head-to-Head Benchmark Scores

Official evaluation metrics verified by independent third-party research labs.

Grok 4.5Grok 4.3
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

74.2%vs71.4%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

75.9%vs73.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

86.8%vs85.2%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1435ptsvs1410pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

13.9%vs12.8%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

49.5%vs47%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

47%vs44.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73.5%vs71.2%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

87.8%vs85%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

87.2%vs88.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs110 tok/s

Latency & Response Time

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Grok 4.50.50s
Grok 4.30.65s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.54.35s
Grok 4.35.20s

Real-Time Interactive Token Cost Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Grok 4.5 Monthly API Bill
$9.15 / month
$2/1M in · $6/1M out
Grok 4.3 Monthly API Bill
$4.59 / month
$1.25/1M in · $2.5/1M out
Grok 4.3 saves approximately $4.56 / month (50%) under this workload.2.0x Savings

Grok 4.5 · Strengths & Key Advantages

  • Substantial price reduction to $2 input and $6 output per million tokens
  • Rapid 130 tokens/sec generation speed with 500ms time-to-first-token
  • Solid reasoning benchmarks across mathematics, logic, and full-stack coding
Considerations & Trade-offs
  • Context window reduced to 500K tokens from earlier 1M variants
  • Superseded in parameter scale and legal depth by Grok 4.7

Grok 4.3 · Strengths & Key Advantages

  • Dependable balance of multi-step reasoning, coding, and multimodal conversation
  • Massive 1M-token context window with significantly suppressed hallucination rates
  • Consistent function calling and JSON output fidelity across complex schemas
Considerations & Trade-offs
  • Trails mid-2026 frontier leaders on PhD-level STEM competitions
  • Output pricing of $15/1M is higher than subsequent Grok 4.5 and 4.7 releases

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGrok 4.5Grok 4.3
Cost per Task
Estimated USD to finish one task
$0.62$1.35
Output Tokens / Task
Tokens generated per task
44K46K
Reasoning Tokens / Task
Thinking tokens burned per task
20K22K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 4.5Grok 4.3
Official API Model ID (SDK)grok-4-5-latestgrok-4-3-latest
API ProtocolxAI REST API (OpenAI-Compatible)xAI REST API (OpenAI-Compatible)
Release Date2026-072026-04
Knowledge CutoffMarch 2026January 2026
ArchitectureAdvanced Sparse MoEColossus-Scale Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 500K windowFlat rate ($1.25/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.5/1M tokensCached input at $0.31/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxReal-time Web & X (Twitter) Search Grounding + Code ExecutionReal-time Web & X (Twitter) Search Grounding + Code Execution
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationxAI Production Safety & Alignment VerifiedxAI Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Grok 4.5 vs Grok 4.3: Quick Answers

Which is more intelligent, Grok 4.5 or Grok 4.3?

Grok 4.5 is more intelligent. It scores 75 compared with 71 on the composite Intelligence Index.

Which model is faster?

Grok 4.5 is faster, generating 130 tokens per second compared with 110 tokens per second.

Which model is cheaper to run?

Grok 4.3 is cheaper at $0.72 per 1M tokens blended, compared with $1.35 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 4.5 has lower latency, with a time to first token of 0.50s compared with 0.65s.

Which model has a larger context window?

Grok 4.3 has a larger context window, supporting 1M tokens compared with 500K tokens.

Verdict

Verdict & Model Selection Recommendation: Choose Grok 4.5 if your priority is Cost-sensitive production APIs, rapid coding assistants, and technical Q&A. Its performance in demanding tasks justifies its operational token cost. Choose Grok 4.3 if your workflow prioritizes Enterprise knowledge retrieval, daily developer assistance, and general-purpose reasoning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Frequently asked questions

How does Grok 4.5 compare to Grok 4.3 in API token pricing and cost per token?+

Grok 4.5 costs $2.00 per 1M input tokens and $6.00 per 1M output tokens, whereas Grok 4.3 costs $1.25 input and $2.50 output. Overall, Grok 4.3 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Grok 4.5 or Grok 4.3?+

Grok 4.5 supports a context window of 500K tokens (~375k words), while Grok 4.3 supports 1,000K tokens (~750k words). Therefore, Grok 4.3 can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Grok 4.5 or Grok 4.3?+

Grok 4.5 scores 74.2% on SWE-bench Verified while Grok 4.3 scores 71.4%. For autonomous software engineering and multi-file debugging, Grok 4.5 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Grok 4.5 and Grok 4.3?+

Grok 4.5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok 4.3 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Grok 4.5 and Grok 4.3?+

Grok 4.5 generates approximately 130 tokens per second, while Grok 4.3 delivers 110 tokens per second. In latency-sensitive production environments, Grok 4.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Grok 4.5 and Grok 4.3 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok 4.3 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 4.5. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Sources: GetInfoUs Independent AI Benchmarks & Official API Specs