Grok 3 Mini vs Claude 3.7 Sonnet
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Grok 3 Mini by xAI and Claude 3.7 Sonnet by Anthropic 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 3 Mini holds a notable pricing advantage for token ingestion. On output generation, Grok 3 Mini is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude 3.7 Sonnet provides an expanded memory horizon with 200K tokens. In latency-sensitive production environments, Grok 3 Mini 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 3 Mini
Deep-Reasoning-ModellGrok 3 Mini von xAI ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 131K Token zu API-Preisen von $0.3/1M Input- und $1.2/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.
$0.30 / 1M
$1.20 / 1M
131.1K tokens
56.4%
Claude 3.7 Sonnet
Deep-Reasoning-ModellClaude 3.7 Sonnet von Anthropic ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 200K Token zu API-Preisen von $3/1M Input- und $15/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.
$3.00 / 1M
$15.00 / 1M
200K tokens
70.3%
Wichtigste Unterschiede auf einen Blick
- Grok 3 Mini is 11.2x cheaper for API usage (input + output tokens combined).
- Claude 3.7 Sonnet has a larger context window (200K vs 131K tokens).
- Grok 3 Mini is faster at 90 tok/s vs 72 tok/s.
- Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 56.4%).
| Feature | Grok 3 Mini | Claude 3.7 Sonnet |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 47 | 48 |
Provider | xAI | Anthropic |
Input Price Cost per million input tokens | $0.30 / 1M | $3.00 / 1M |
Output Price Cost per million output tokens | $1.20 / 1M | $15.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.23 / 1M | $2.31 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 16K | 64K |
Throughput Speed Tokens generated per second | 90 tok/s | 72 tok/s |
SWE-bench Verified Real-world software engineering | 56.4% | 70.3% |
GPQA Diamond Graduate-level reasoning | 68.4% | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.07 / 1M | $0.30 / 1M |
Wer gewinnt in welcher Disziplin?
At-a-glance decision frameworkGeprüfte Benchmark-Ergebnisse im Vergleich
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.
Latenz & Antwortzeit
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Interaktiver Token-Kosten-Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Grok 3 Mini · Strengths & Key Advantages
- Fortschrittliche Reasoning Optimized Hybrid Transformer-Architektur von xAI mit 131K Token Kontextfenster
- Starkes Preis-Leistungs-Verhältnis ($0.3/1M Input, $1.2/1M Output) bei hoher Durchsatzrate
- Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
- Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
- Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering
Claude 3.7 Sonnet · Strengths & Key Advantages
- Fortschrittliche Hybrid Reasoning MoE-Architektur von Anthropic mit 200K Token Kontextfenster
- Starkes Preis-Leistungs-Verhältnis ($3/1M Input, $15/1M Output) bei hoher Durchsatzrate
- Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
- Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
- Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 3 Mini | Claude 3.7 Sonnet |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.32 | $1.42 |
Output Tokens / Task Tokens generated per task | 26K | 41K |
Reasoning Tokens / Task Thinking tokens burned per task | 18K | 22K |
Technische Spezifikationen
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok 3 Mini | Claude 3.7 Sonnet |
|---|---|---|
| Official API Model ID (SDK) | grok-3-mini-latest | claude-3-7-sonnet-20250201 |
| API Protocol | xAI REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2025-02 | 2025-02 |
| Knowledge Cutoff | November 2024 | November 2024 |
| Architecture | Reasoning Optimized Hybrid Transformer | Hybrid Reasoning MoE |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.3/1M in) across full 131K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.075/1M tokens | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| 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 | text, vision |
| Output Modalities | text | text |
Grok 3 Mini vs Claude 3.7 Sonnet: Schnelle Antworten (FAQ)
Which is more intelligent, Grok 3 Mini or Claude 3.7 Sonnet?
Claude 3.7 Sonnet is more intelligent. It scores 48 compared with 47 on the composite Intelligence Index.
Which model is faster?
Grok 3 Mini is faster, generating 90 tokens per second compared with 72 tokens per second.
Which model is cheaper to run?
Grok 3 Mini is cheaper at $0.23 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok 3 Mini has lower latency, with a time to first token of 0.51s compared with 0.52s.
Which model has a larger context window?
Claude 3.7 Sonnet has a larger context window, supporting 200K tokens compared with 131.1K tokens.
Fazit
Verdict & Model Selection Recommendation: Choose Grok 3 Mini if your priority is Automated code reviews, real-time debugging agents, and mathematical data analysis. Its performance in demanding tasks justifies its operational token cost. Choose Claude 3.7 Sonnet if your workflow prioritizes Full-stack software architecture, complex refactoring, and agentic workflows. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Häufig gestellte Fragen (FAQ)
How does Grok 3 Mini compare to Claude 3.7 Sonnet in API token pricing and cost per token?+
Grok 3 Mini costs $0.30 per 1M input tokens and $1.20 per 1M output tokens, whereas Claude 3.7 Sonnet costs $3.00 input and $15.00 output. Overall, Grok 3 Mini 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 3 Mini or Claude 3.7 Sonnet?+
Grok 3 Mini supports a context window of 131K tokens (~98k words), while Claude 3.7 Sonnet supports 200K tokens (~150k words). Therefore, Claude 3.7 Sonnet can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok 3 Mini or Claude 3.7 Sonnet?+
Grok 3 Mini scores 56.4% on SWE-bench Verified while Claude 3.7 Sonnet scores 70.3%. For autonomous software engineering and multi-file debugging, Claude 3.7 Sonnet holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 3 Mini and Claude 3.7 Sonnet?+
Grok 3 Mini features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude 3.7 Sonnet provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Grok 3 Mini and Claude 3.7 Sonnet?+
Grok 3 Mini generates approximately 90 tokens per second, while Claude 3.7 Sonnet delivers 72 tokens per second. In latency-sensitive production environments, Grok 3 Mini provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok 3 Mini and Claude 3.7 Sonnet to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok 3 Mini to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3.7 Sonnet. This tiered routing pattern cuts overall API bills by up to 70%.
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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- Grok-3 vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed ComparisonVergleich
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.
Offizielle Quellen: GetInfoUs Independent AI Benchmarks & Official API Specs