Gemini 3.1 Pro Google 2000000
💰 Total Cost Calculation (from Plugin)
Output: $0.030000
Output: $0.030000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 5,000 output tokens:
- Input Cost: $0.050000
- Output Cost: $0.030000
- Total Cost: $0.062000 (rounded ~ $0.06)
- Cost per 1K tokens: $0.001127
- Tokens per dollar: 887,097 tokens
- Context Window: 2000000 tokens
Speed & Performance Analysis
With a processing speed of 400 tokens per second and 220ms time to first token:
- Processing Time: 2 minutes, 27.31 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 374 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Gemini 3.1 Pro| Rank | AI Model & Provider | Total Cost | vs Gemini 3.1 Pro |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001175 Best Value | ↓ 98.1% cheaper |
| 🥈 |
Grok Code Fast 1
xAI
|
$0.003475 | ↓ 94.4% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.003875 | ↓ 93.8% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.005525 (rounded ~ $0.01) | ↓ 91.1% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.005875 (rounded ~ $0.01) | ↓ 90.5% cheaper |
| #6 |
GPT-5.4 mini
OpenAI
|
$0.011625 (rounded ~ $0.01) | ↓ 81.3% cheaper |
| #7 |
o4-mini Deep Research
OpenAI
|
$0.013000 (rounded ~ $0.01) | ↓ 79% cheaper |
| #8 |
Grok 4.3
xAI
|
$0.013125 (rounded ~ $0.01) | ↓ 78.8% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.014250 (rounded ~ $0.01) | ↓ 77% cheaper |
| #10 |
o4-mini
OpenAI
|
$0.014300 (rounded ~ $0.01) | ↓ 76.9% cheaper |
| #11 |
Gemini 3.1 Flash
Google
|
$0.015500 (rounded ~ $0.02) | ↓ 75% cheaper |
| #12 |
Gemini 3.5 Flash
Google
|
$0.023250 (rounded ~ $0.02) | ↓ 62.5% cheaper |
| #13 |
Grok 4.20 Beta
xAI
|
$0.023500 (rounded ~ $0.02) | ↓ 62.1% cheaper |
| #14 |
GPT-5.3 Codex Spark
OpenAI
|
$0.031500 (rounded ~ $0.03) | ↓ 49.2% cheaper |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.031500 (rounded ~ $0.03) | ↓ 49.2% cheaper |
| #16 |
Claude Sonnet 4.6
Anthropic
|
$0.042750 (rounded ~ $0.04) | ↓ 31% cheaper |
| #17 |
Gemini 2.5 Pro
Google
|
$0.045000 (rounded ~ $0.05) | ↓ 27.4% cheaper |
| #18 |
Claude Opus 4.7
Anthropic
|
$0.071250 (rounded ~ $0.07) | ↑ 14.9% more |
| #19 |
Claude Opus 4.8
Anthropic
|
$0.071250 (rounded ~ $0.07) | ↑ 14.9% more |
| #20 |
Claude Opus 4.6
Anthropic
|
$0.071250 (rounded ~ $0.07) | ↑ 14.9% more |
| #21 |
GPT-5.4
OpenAI
|
$0.077500 (rounded ~ $0.08) | ↑ 25% more |
| #22 |
GPT-5.4 Thinking
OpenAI
|
$0.077500 (rounded ~ $0.08) | ↑ 25% more |
| #23 |
GPT-5.5 Instant
OpenAI
|
$0.077500 (rounded ~ $0.08) | ↑ 25% more |
| #24 |
o3 Deep Research
OpenAI
|
$0.130000 | ↑ 109.7% more |
| #25 |
GPT-5.5
OpenAI
|
$0.155000 (rounded ~ $0.16) | ↑ 150% more |
| #26 |
o3 Pro
OpenAI
|
$0.260000 | ↑ 319.4% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.378000 (rounded ~ $0.38) | ↑ 509.7% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$0.378000 (rounded ~ $0.38) | ↑ 509.7% more |
Mistral Small 3 Mistral AI
Grok Code Fast 1 xAI
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Grok 4.3 xAI
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Gemini 3.1 Flash Google
Gemini 3.5 Flash Google
Grok 4.20 Beta xAI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 4.6 Anthropic
Gemini 2.5 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
o3 Deep Research OpenAI
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Planning Your AI Budget: Gemini 3.1 Pro for Daily Code Review at 50,000 Tokens
This record focuses on budget planning for a code review assistant, using Gemini 3.1 Pro to process approximately 50,000 tokens per day. This daily volume is a realistic workload for a small development team or an individual indie hacker managing multiple projects. Understanding the costs associated with this scale is vital for sustainable AI deployment.
Gemini 3.1 Pro: A Powerful All-Rounder
Google’s Gemini 3.1 Pro is a highly capable multimodal model featuring a massive 2,000,000 token context window. Its pricing is tiered, starting at $2 per 1 million input tokens. For a daily usage of 50,000 tokens, the estimated daily cost is approximately $0.10. This translates to a monthly cost of roughly $3.00 for this specific workload (assuming 30 days).
The model’s extensive capabilities—text, vision, audio, video, tools, and advanced thinking—make it an exceptional choice for comprehensive code analysis. For code review, this means it can not only understand code logic but also interpret visual elements if necessary, leverage external information via tools, and provide in-depth reasoning for its suggestions.
- Model Name: Gemini 3.1 Pro
- Provider: Google
- Context Window: 2,000,000 tokens
- Pricing (per 1M tokens): $2 (input) / $12 (output) – tiered
- Estimated Daily Cost for 50K Tokens: ~$0.10
- Key Capabilities: text, vision, audio, video, tools, thinking
Code Review Assistant Workflow
A code review assistant powered by Gemini 3.1 Pro at 50,000 tokens per day can offer significant value. It can analyze pull requests, identify potential bugs, security vulnerabilities, performance bottlenecks, and adherence to coding standards. The ‘thinking’ capability allows for more nuanced feedback, such as suggesting alternative implementations or explaining complex code sections.
The ‘tools’ capability is particularly powerful. It can be integrated with code repositories, CI/CD pipelines, or external documentation services to fetch relevant context, verify findings, or even automatically suggest code patches. This makes the AI assistant more than just a text processor; it becomes an active participant in the development workflow.
For academic researchers and indie developers, the ability to forecast monthly expenses based on daily token usage is invaluable. A cost of ~$3 per month for this level of AI assistance per project is highly accessible, allowing for the development and deployment of sophisticated AI tools even on a shoestring budget.
Best Use Cases: Comprehensive code analysis, intelligent development assistants, multimodal research tasks, and projects requiring advanced reasoning and tool integration with predictable monthly costs.