Gemini 3.6 Flash Google 1048576
💰 Total Cost Calculation (from Plugin)
Output: $0.150000
Output: $0.150000
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 20,000 output tokens:
- Input Cost: $0.150000
- Output Cost: $0.150000
- Total Cost: $0.219000 (rounded ~ $0.22)
- Cost per 1K tokens: $0.001825
- Tokens per dollar: 547,945 tokens
- Context Window: 1048576 tokens
Speed & Performance Analysis
With a processing speed of 304 tokens per second and 120ms time to first token:
- Processing Time: 7 minutes, 2.55 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 304 tokens/second
- Effective Throughput: 284 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Gemini 3.6 Flash| Rank | AI Model & Provider | Total Cost | vs Gemini 3.6 Flash |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.010600 Best Value | ↓ 95.2% cheaper |
| 🥈 |
Grok Code Fast 1
xAI
|
$0.039200 | ↓ 82.1% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.041500 (rounded ~ $0.04) | ↓ 81.1% cheaper |
| #4 |
Mistral Large 3
Mistral AI
|
$0.053000 (rounded ~ $0.05) | ↓ 75.8% cheaper |
| #5 |
Gemini 3.5 Flash-Lite
Google
|
$0.063800 (rounded ~ $0.06) | ↓ 70.9% cheaper |
| #6 |
Gemini 2.5 Flash
Google
|
$0.063800 (rounded ~ $0.06) | ↓ 70.9% cheaper |
| #7 |
Gemini 3.1 Flash
Google
|
$0.083000 (rounded ~ $0.08) | ↓ 62.1% cheaper |
| #8 |
Grok Build 0.1
xAI
|
$0.086000 (rounded ~ $0.09) | ↓ 60.7% cheaper |
| #9 |
Kimi K2.5
Moonshot AI
|
$0.090120 | ↓ 58.8% cheaper |
| #10 |
Grok 4.3
xAI
|
$0.107500 (rounded ~ $0.11) | ↓ 50.9% cheaper |
| #11 |
Grok 4.20 Beta
xAI
|
$0.107500 (rounded ~ $0.11) | ↓ 50.9% cheaper |
| #12 |
Gemini 3.8 Flash
Google
|
$0.109500 | ↓ 50% cheaper |
| #13 |
GPT-5.4 mini
OpenAI
|
$0.124500 (rounded ~ $0.12) | ↓ 43.2% cheaper |
| #14 |
o4-mini Deep Research
OpenAI
|
$0.126000 (rounded ~ $0.13) | ↓ 42.5% cheaper |
| #15 |
Kimi K2.6
Moonshot AI
|
$0.127690 (rounded ~ $0.13) | ↓ 41.7% cheaper |
| #16 |
Kimi K2.7 Code
Moonshot AI
|
$0.127690 (rounded ~ $0.13) | ↓ 41.7% cheaper |
| #17 |
o4-mini
OpenAI
|
$0.138600 (rounded ~ $0.14) | ↓ 36.7% cheaper |
| #18 |
Claude Haiku 4.5
Anthropic
|
$0.146000 (rounded ~ $0.15) | ↓ 33.3% cheaper |
| #19 |
GPT-5.6 Luna
OpenAI
|
$0.166000 (rounded ~ $0.17) | ↓ 24.2% cheaper |
| #20 |
Grok 4.6
xAI
|
$0.212000 (rounded ~ $0.21) | ↓ 3.2% cheaper |
| #21 |
Grok 4.5
xAI
|
$0.212000 (rounded ~ $0.21) | ↓ 3.2% cheaper |
| #22 |
Gemini 3.5 Flash
Google
|
$0.249000 (rounded ~ $0.25) | ↑ 13.7% more |
| #23 |
Gemini 2.5 Pro
Google
|
$0.257500 (rounded ~ $0.26) | ↑ 17.6% more |
| #24 |
Claude Sonnet 5
Anthropic
|
$0.292000 (rounded ~ $0.29) | ↑ 33.3% more |
| #25 |
Gemini 3.1 Pro
Google
|
$0.332000 (rounded ~ $0.33) | ↑ 51.6% more |
| #26 |
GPT-5.3 Codex Spark
OpenAI
|
$0.360500 | ↑ 64.6% more |
| #27 |
GPT-5.3 Instant
OpenAI
|
$0.360500 | ↑ 64.6% more |
| #28 |
GPT-5.4
OpenAI
|
$0.415000 (rounded ~ $0.42) | ↑ 89.5% more |
| #29 |
GPT-5.4 Thinking
OpenAI
|
$0.415000 (rounded ~ $0.42) | ↑ 89.5% more |
| #30 |
GPT-5.6 Terra
OpenAI
|
$0.415000 (rounded ~ $0.42) | ↑ 89.5% more |
| #31 |
Claude Sonnet 4.6
Anthropic
|
$0.438000 (rounded ~ $0.44) | ↑ 100% more |
| #32 |
Claude Opus 4.7
Anthropic
|
$0.730000 | ↑ 233.3% more |
| #33 |
Claude Opus 5
Anthropic
|
$0.730000 | ↑ 233.3% more |
| #34 |
Claude Opus 4.8
Anthropic
|
$0.730000 | ↑ 233.3% more |
| #35 |
Claude Opus 4.6
Anthropic
|
$0.730000 | ↑ 233.3% more |
| #36 |
GPT-5.5
OpenAI
|
$0.830000 | ↑ 279% more |
| #37 |
GPT-5.5 Instant
OpenAI
|
$0.830000 | ↑ 279% more |
| #38 |
GPT-5.6 Sol
OpenAI
|
$0.830000 | ↑ 279% more |
| #39 |
o3 Deep Research
OpenAI
|
$1.260000 | ↑ 475.3% more |
| #40 |
Claude Fable 5.1
Anthropic
|
$1.415000 (rounded ~ $1.42) | ↑ 546.1% more |
| #41 |
Claude Mythos 5.1
Anthropic
|
$1.415000 (rounded ~ $1.42) | ↑ 546.1% more |
| #42 |
Claude Fable 5
Anthropic
|
$1.460000 | ↑ 566.7% more |
| #43 |
Claude Mythos 5
Anthropic
|
$1.460000 | ↑ 566.7% more |
| #44 |
GPT-6 Astra
OpenAI
|
$1.460000 | ↑ 566.7% more |
| #45 |
o3 Pro
OpenAI
|
$2.520000 | ↑ 1050.7% more |
| #46 |
GPT-5.2 Pro
OpenAI
|
$4.326000 (rounded ~ $4.33) | ↑ 1875.3% more |
| #47 |
GPT-5.2 Pro
OpenAI
|
$4.326000 (rounded ~ $4.33) | ↑ 1875.3% more |
Mistral Small 3 Mistral AI
Grok Code Fast 1 xAI
Gemini 3.1 Flash Lite Google
Mistral Large 3 Mistral AI
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.1 Flash Google
Grok Build 0.1 xAI
Kimi K2.5 Moonshot AI
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Kimi K2.6 Moonshot AI
Kimi K2.7 Code Moonshot AI
o4-mini OpenAI
Claude Haiku 4.5 Anthropic
GPT-5.6 Luna OpenAI
Grok 4.6 xAI
Grok 4.5 xAI
Gemini 3.5 Flash Google
Gemini 2.5 Pro Google
Claude Sonnet 5 Anthropic
Gemini 3.1 Pro Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
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
GPT-5.5 OpenAI
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
o3 Deep Research OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-6 Astra OpenAI
o3 Pro OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Gemini 3.6 Flash has emerged as a pragmatic favorite for developers scaling customer support agents that need to balance speed, cost, and intelligence. In high-volume support environments where latency directly impacts user satisfaction, Gemini 3.6 Flash offers a compelling performance profile. It is engineered to deliver rapid, accurate responses while maintaining the efficiency required for running hundreds of concurrent agent sessions without excessive overhead.
What makes this model particularly well-suited for support agents is its native multimodal reasoning. Modern support isn’t just text; customers frequently upload screenshots of error messages, PDFs of invoices, or short video clips of UI bugs. Gemini 3.6 Flash processes these inputs with low latency, allowing your agents to provide contextual, visual-aware assistance that standard text-only models would miss. For indie hackers and MVPs looking to build agents that handle diverse ticket types—from routine status checks to more complex troubleshooting—it serves as a reliable workhorse. Its capability to effectively orchestrate tools ensures that it can not only answer questions but also initiate the necessary actions to resolve them. By focusing on high-throughput, latency-optimized performance, Gemini 3.6 Flash allows you to build a responsive, enterprise-grade support layer that grows with your user base without the cost complexity of larger, frontier-tier reasoning models.