Grok 4.5 xAI 🏔️ Context Cliff
💰 Total Cost Calculation (from Plugin)
Output: $0.024000 (rounded ~ $0.02)
Output: $0.024000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 2,000 output tokens:
- Input Cost: $2.000000
- Output Cost: $0.024000 (rounded ~ $0.02)
- Total Cost: $1.304000 (rounded ~ $1.30)
- Cost per 1K tokens: $0.002598
- Tokens per dollar: 384,969 tokens
- Context Window: 500000 tokens
Speed & Performance Analysis
With a processing speed of 90 tokens per second and 210ms time to first token:
- Processing Time: 1 hour, 37 minutes, 36.85 seconds
- Latency: 210 milliseconds to first token
- Base Throughput: 90 tokens/second
- Effective Throughput: 86 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Grok 4.5| Rank | AI Model & Provider | Total Cost | vs Grok 4.5 |
|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.020750 Best Value | ↓ 98.4% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.025250 (rounded ~ $0.03) | ↓ 98.1% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.025250 (rounded ~ $0.03) | ↓ 98.1% cheaper |
| #4 |
Gemini 3.8 Flash
Google
|
$0.061875 (rounded ~ $0.06) | ↓ 95.3% cheaper |
| #5 |
GPT-5.6 Luna
OpenAI
|
$0.083000 (rounded ~ $0.08) | ↓ 93.6% cheaper |
| #6 |
Gemini 3.6 Flash
Google
|
$0.123750 (rounded ~ $0.12) | ↓ 90.5% cheaper |
| #7 |
Gemini 3.5 Flash
Google
|
$0.124500 (rounded ~ $0.12) | ↓ 90.5% cheaper |
| #8 |
Claude Sonnet 5
Anthropic
|
$0.165000 (rounded ~ $0.17) | ↓ 87.3% cheaper |
| #9 |
Gemini 3.1 Flash
Google
|
$0.166000 (rounded ~ $0.17) | ↓ 87.3% cheaper |
| #10 |
GPT-5.6 Terra
OpenAI
|
$0.207500 (rounded ~ $0.21) | ↓ 84.1% cheaper |
| #11 |
Claude Sonnet 4.6
Anthropic
|
$0.247500 (rounded ~ $0.25) | ↓ 81% cheaper |
| #12 |
Claude Opus 4.7
Anthropic
|
$0.412500 (rounded ~ $0.41) | ↓ 68.4% cheaper |
| #13 |
Claude Opus 5
Anthropic
|
$0.412500 (rounded ~ $0.41) | ↓ 68.4% cheaper |
| #14 |
Claude Opus 4.8
Anthropic
|
$0.412500 (rounded ~ $0.41) | ↓ 68.4% cheaper |
| #15 |
Claude Opus 4.6
Anthropic
|
$0.412500 (rounded ~ $0.41) | ↓ 68.4% cheaper |
| #16 |
Gemini 2.5 Pro
Google
|
$0.415000 (rounded ~ $0.42) | ↓ 68.2% cheaper |
| #17 |
GPT-5.6 Sol
OpenAI
|
$0.415000 (rounded ~ $0.42) | ↓ 68.2% cheaper |
| #18 |
Grok 4.3
xAI
|
$0.648000 (rounded ~ $0.65) | ↓ 50.3% cheaper |
| #19 |
Grok 4.20 Beta
xAI
|
$0.648000 (rounded ~ $0.65) | ↓ 50.3% cheaper |
| #20 |
Gemini 3.1 Pro
Google
|
$0.658000 (rounded ~ $0.66) | ↓ 49.5% cheaper |
| #21 |
Claude Fable 5.1
Anthropic
|
$0.787500 (rounded ~ $0.79) | ↓ 39.6% cheaper |
| #22 |
Claude Mythos 5.1
Anthropic
|
$0.787500 (rounded ~ $0.79) | ↓ 39.6% cheaper |
| #23 |
GPT-5.4
OpenAI
|
$0.822500 (rounded ~ $0.82) | ↓ 36.9% cheaper |
| #24 |
GPT-5.4 Thinking
OpenAI
|
$0.822500 (rounded ~ $0.82) | ↓ 36.9% cheaper |
| #25 |
Claude Fable 5
Anthropic
|
$0.825000 (rounded ~ $0.83) | ↓ 36.7% cheaper |
| #26 |
Claude Mythos 5
Anthropic
|
$0.825000 (rounded ~ $0.83) | ↓ 36.7% cheaper |
| #27 |
GPT-5.5
OpenAI
|
$1.645000 (rounded ~ $1.65) | ↑ 26.2% more |
| #28 |
GPT-6 Astra
OpenAI
|
$3.300000 | ↑ 153.1% more |
| #29 |
GPT-6 Astra
OpenAI
|
$3.300000 | ↑ 153.1% more |
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
Gemini 2.5 Pro Google
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
Grok 4.5, introduced in July 2026, has quickly become a focal point for engineers building agentic workflows that require deep context handling. With a 500K-token context window, it provides substantial space for maintaining long conversation states or analyzing large codebases, which is a common requirement for complex multi-agent orchestration tasks.
What sets Grok 4.5 apart in agentic settings is its integration with developer-centric tools. Having been trained alongside real-world software engineering interactions, it shows a strong capability for repository-wide refactoring and complex coding agent loops. When you are feeding 500K tokens of context into an agentic pipeline, you need a model that doesn’t just hold the data but reasons effectively across the entire span to identify dependencies and potential logic errors.
However, it is important to match Grok 4.5 to the right tasks. While it excels in structured engineering and coding, users should be mindful of its behavior in open-ended or highly creative tasks where its logic can differ from more generalized frontier models. For teams that have already adopted agentic architectures and are looking for a high-performance, developer-focused model to handle long-running sub-agent chains, Grok 4.5 offers a distinctive balance of reasoning and context availability that is difficult to replicate with smaller, faster models. It is particularly well-suited for backend feature work, migration tasks, and any scenario where the agent needs to inspect live codebases or multiple files before suggesting changes.