Gemini 3.1 Flash Lite Google 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.000750
Output: $0.000750
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Multimodal Input Details
Resolution: Medium
Tokens: 5,160,000
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 2,000 input tokens and 500 output tokens:
- Input Cost: $1.290500
- Output Cost: $0.000750
- Total Cost: $1.291250 (rounded ~ $1.29)
- Cost per 1K tokens: $0.000250
- Tokens per dollar: 3,998,064 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 1,000 tokens per second and 80ms time to first token:
- Processing Time: 1 hour, 32 minutes, 4.06 seconds
- Latency: 80 milliseconds to first token
- Base Throughput: 1,000 tokens/second
- Effective Throughput: 935 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Gemini 3.1 Flash Lite| Rank | AI Model & Provider | Total Cost | vs Gemini 3.1 Flash Lite |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.516350 (rounded ~ $0.52) Best Value | ↓ 60% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$1.549850 | ↑ 20% more |
| 🥉 |
Gemini 2.5 Flash
Google
|
$1.549850 | ↑ 20% more |
| #4 |
Llama 4 Maverick (400B)
Meta AI
|
$2.415600 (rounded ~ $2.42) | ↑ 87.1% more |
| #5 |
Mistral Large 3
Mistral AI
|
$2.582750 (rounded ~ $2.58) | ↑ 100% more |
| #6 |
Kimi K2.5
Moonshot AI
|
$3.098700 (rounded ~ $3.10) | ↑ 140% more |
| #7 |
Gemini 3.8 Flash
Google
|
$3.873375 (rounded ~ $3.87) | ↑ 200% more |
| #8 |
GPT-5.4 mini
OpenAI
|
$3.873750 (rounded ~ $3.87) | ↑ 200% more |
| #9 |
Kimi K2.6
Moonshot AI
|
$4.905900 (rounded ~ $4.91) | ↑ 279.9% more |
| #10 |
Kimi K2.7 Code
Moonshot AI
|
$4.905900 (rounded ~ $4.91) | ↑ 279.9% more |
| #11 |
o4-mini Deep Research
OpenAI
|
$5.164000 (rounded ~ $5.16) | ↑ 299.9% more |
| #12 |
Claude Haiku 4.5
Anthropic
|
$5.164500 (rounded ~ $5.16) | ↑ 300% more |
| #13 |
Gemini 3.1 Flash
Google
|
$5.165000 (rounded ~ $5.17) | ↑ 300% more |
| #14 |
GPT-5.6 Luna
OpenAI
|
$5.165000 (rounded ~ $5.17) | ↑ 300% more |
| #15 |
o4-mini
OpenAI
|
$5.680400 | ↑ 339.9% more |
| #16 |
Muse Spark 1.3
Meta AI
|
$6.454625 (rounded ~ $6.45) | ↑ 399.9% more |
| #17 |
Gemini 3.6 Flash
Google
|
$7.746750 (rounded ~ $7.75) | ↑ 499.9% more |
| #18 |
Gemini 3.5 Flash
Google
|
$7.747500 (rounded ~ $7.75) | ↑ 500% more |
| #19 |
GPT-5.3 Codex Spark
OpenAI
|
$9.040500 | ↑ 600.1% more |
| #20 |
GPT-5.3 Instant
OpenAI
|
$9.040500 | ↑ 600.1% more |
| #21 |
Claude Sonnet 5
Anthropic
|
$10.329000 | ↑ 699.9% more |
| #22 |
Grok 4.3
xAI
|
$12.907500 (rounded ~ $12.91) | ↑ 899.6% more |
| #23 |
Gemini 2.5 Pro
Google
|
$12.912500 (rounded ~ $12.91) | ↑ 900% more |
| #24 |
GPT-5.6 Terra
OpenAI
|
$12.912500 (rounded ~ $12.91) | ↑ 900% more |
| #25 |
Claude Sonnet 4.6
Anthropic
|
$15.493500 (rounded ~ $15.49) | ↑ 1099.9% more |
| #26 |
Grok 4.6
xAI
|
$20.654000 (rounded ~ $20.65) | ↑ 1499.5% more |
| #27 |
Grok 4.5
xAI
|
$20.654000 (rounded ~ $20.65) | ↑ 1499.5% more |
| #28 |
Gemini 3.1 Pro
Google
|
$20.657000 (rounded ~ $20.66) | ↑ 1499.8% more |
| #29 |
GPT-5.4
OpenAI
|
$25.821250 (rounded ~ $25.82) | ↑ 1899.7% more |
| #30 |
GPT-5.4 Thinking
OpenAI
|
$25.821250 (rounded ~ $25.82) | ↑ 1899.7% more |
| #31 |
Claude Opus 4.7
Anthropic
|
$25.822500 (rounded ~ $25.82) | ↑ 1899.8% more |
| #32 |
Claude Opus 5
Anthropic
|
$25.822500 (rounded ~ $25.82) | ↑ 1899.8% more |
| #33 |
Claude Opus 4.8
Anthropic
|
$25.822500 (rounded ~ $25.82) | ↑ 1899.8% more |
| #34 |
Claude Opus 4.6
Anthropic
|
$25.822500 (rounded ~ $25.82) | ↑ 1899.8% more |
| #35 |
GPT-5.5 Instant
OpenAI
|
$25.825000 (rounded ~ $25.83) | ↑ 1900% more |
| #36 |
GPT-5.6 Sol
OpenAI
|
$25.825000 (rounded ~ $25.83) | ↑ 1900% more |
| #37 |
o3 Deep Research
OpenAI
|
$51.640000 | ↑ 3899.2% more |
| #38 |
GPT-5.5
OpenAI
|
$51.642500 (rounded ~ $51.64) | ↑ 3899.4% more |
| #39 |
Claude Fable 5.1
Anthropic
|
$51.645000 (rounded ~ $51.65) | ↑ 3899.6% more |
| #40 |
Claude Mythos 5.1
Anthropic
|
$51.645000 (rounded ~ $51.65) | ↑ 3899.6% more |
| #41 |
Claude Fable 5
Anthropic
|
$51.645000 (rounded ~ $51.65) | ↑ 3899.6% more |
| #42 |
Claude Mythos 5
Anthropic
|
$51.645000 (rounded ~ $51.65) | ↑ 3899.6% more |
| #43 |
o3 Pro
OpenAI
|
$103.280000 | ↑ 7898.5% more |
| #44 |
GPT-6 Astra
OpenAI
|
$103.290000 | ↑ 7899.2% more |
| #45 |
GPT-5.2 Pro
OpenAI
|
$108.486000 (rounded ~ $108.49) | ↑ 8301.6% more |
| #46 |
GPT-5.5 Pro
OpenAI
|
$154.950000 | ↑ 11900% more |
| #47 |
GPT-5.5 Pro
OpenAI
|
$154.950000 | ↑ 11900% more |
Mistral Small 3 Mistral AI
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Llama 4 Maverick (400B) Meta AI
Mistral Large 3 Mistral AI
Kimi K2.5 Moonshot AI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
Kimi K2.6 Moonshot AI
Kimi K2.7 Code Moonshot AI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Muse Spark 1.3 Meta AI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
Grok 4.3 xAI
Gemini 2.5 Pro Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Grok 4.6 xAI
Grok 4.5 xAI
Gemini 3.1 Pro Google
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
o3 Deep Research OpenAI
GPT-5.5 OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.5 Pro OpenAI
GPT-5.5 Pro OpenAI
When cost-effectiveness is paramount for generating up to 10,000 storyboard frames, Gemini 3.1 Flash Lite emerges as a compelling option. This model balances essential vision capabilities with efficient text processing, making it suitable for creating numerous visual assets and accompanying scene descriptions without prohibitive expense. For SaaS founders and mid-market teams scaling creative features, its affordability per image is a significant advantage. Consultants should evaluate its ability to maintain visual consistency and interpret scene prompts accurately at scale. While it may not match the nuanced creative output of higher-tier models, its efficiency makes it ideal for rapid prototyping or large-volume content generation where budget constraints are a primary driver for AI model selection.