Grok 4.5 vs Grok 4.7
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok 4.5 by xAI and Grok 4.7 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, both models offer identical input token rates. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 500K 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.
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Grok 4.5
Fast ReasoningHigh-throughput, budget-friendly generalist combining fast hybrid reasoning with reduced API pricing of $2/$6 per million tokens.
$2.00 / 1M
$6.00 / 1M
500K tokens
74.2%
Grok 4.7
Same-Price Upgrade2.1 Trillion parameter powerhouse with four-tier adjustable reasoning, top legal agent scores, and unchanged $2/$6 pricing.
$2.00 / 1M
$6.00 / 1M
500K tokens
77.2%
Key Differences at a Glance
- Both models cost the same under this workload — choose on capability, not price.
- Grok 4.5 is faster at 130 tok/s vs 110 tok/s.
- Grok 4.7 leads on SWE-bench coding (77.2% vs 74.2%).
| Feature | Grok 4.5 | Grok 4.7 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 46 |
Provider | xAI | xAI |
Input Price Cost per million input tokens | $2.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $6.00 / 1M | $6.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.35 / 1M | $1.35 / 1M |
Context Window Maximum input + output tokens | 500K tokens~750 A4 pages of text | 500K tokens~750 A4 pages of text |
Max Output Tokens Per single request | 66K | 66K |
Throughput Speed Tokens generated per second | 130 tok/s | 110 tok/s |
SWE-bench Verified Real-world software engineering | 74.2% | 77.2% |
GPQA Diamond Graduate-level reasoning | 75.9% | 78.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.50 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
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 4.7 · Strengths & Key Advantages
- Massive 2.1T MoE parameter scale with unchanged base pricing ($2 in / $6 out per 1M)
- 4-level reasoning effort control with top legal agent score (Harvey Legal 19.6%)
- High biology and scientific synthesis performance (LatchBio 62.4%)
- Strong official CursorBench (46.3) and Terminal-Bench (38.0) performance
Considerations & Trade-offs
- Independent benchmarks show lower scores than official claims (Terminal-Bench ~26% vs 38%)
- Long-context queries (>=200K) double the effective API pricing ($4 in / $12 out) across the entire request
- Multimodal image reasoning remains somewhat weaker than competing vision flagships
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 4.5 | Grok 4.7 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.62 | $0.68 |
Output Tokens / Task Tokens generated per task | 44K | 46K |
Reasoning Tokens / Task Thinking tokens burned per task | 20K | 23K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok 4.5 | Grok 4.7 |
|---|---|---|
| Official API Model ID (SDK) | grok-4-5-latest | grok-4-7-latest |
| API Protocol | xAI REST API (OpenAI-Compatible) | xAI REST API (OpenAI-Compatible) |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | March 2026 | April 2026 |
| Architecture | Advanced Sparse MoE | 2.1T Multimodal Sparse MoE |
| Parameters | Confidential | 2.1T (MoE) |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 500K window | Flat rate ($2/1M in) across full 500K window |
| Prompt Cache Policy & TTL | Cached input at $0.5/1M tokens | Cached input at $0.5/1M tokens |
| Computer Use / GUI Agent | API / 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 Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Real-time Web & X (Twitter) Search Grounding + Code Execution | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text 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 VRAM | Cloud-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 Classification | xAI Production Safety & Alignment Verified | xAI Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
Grok 4.5 vs Grok 4.7: Quick Answers
Which is more intelligent, Grok 4.5 or Grok 4.7?
Grok 4.5 is more intelligent. It scores 75 compared with 46 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 has lower latency?
Grok 4.5 has lower latency, with a time to first token of 0.50s compared with 0.62s.
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 4.7 if your workflow prioritizes Affordable second opinions in coding and legal workflows, enterprise domain tasks, and balanced agentic automation. 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 4.7 in API token pricing and cost per token?+
Both Grok 4.5 and Grok 4.7 share matched API token pricing at $2.00 per 1M input tokens and $6.00 per 1M output tokens. Because their token economics are identical, your selection should be guided by benchmark latency, memory horizon, and reasoning capabilities rather than operational token fees. 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 4.7?+
Both Grok 4.5 and Grok 4.7 offer an identical context window of 500K tokens (~375k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Grok 4.5 or Grok 4.7?+
Grok 4.5 scores 74.2% on SWE-bench Verified while Grok 4.7 scores 77.2%. For autonomous software engineering and multi-file debugging, Grok 4.7 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 4.5 and Grok 4.7?+
Grok 4.5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok 4.7 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 4.7?+
Grok 4.5 generates approximately 130 tokens per second, while Grok 4.7 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 4.7 to optimize costs?+
Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to Grok 4.5, and route deep architectural or complex reasoning queries to Grok 4.5. This balanced routing strategy maximizes system throughput and answer quality.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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