Claude Sonnet 5.5 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.080000
Output: $0.080000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 32,000 input tokens and 32,000 output tokens:
- Input Cost: $0.016000 (rounded ~ $0.02)
- Output Cost: $0.080000
- Total Cost: $0.088400 (rounded ~ $0.09)
- Cost per 1K tokens: $0.001381
- Tokens per dollar: 723,982 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 300 tokens per second and 300ms time to first token:
- Processing Time: 3 minutes, 48.45 seconds
- Latency: 300 milliseconds to first token
- Base Throughput: 300 tokens/second
- Effective Throughput: 280 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Claude Sonnet 5.5| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 5.5 |
|---|---|---|---|
| 🏆 |
Ministral 3 (14B)
Mistral AI
|
$0.002480 Best Value | ↓ 97.2% cheaper |
| 🥈 |
Nemotron 3 Super
NVIDIA
|
$0.007880 (rounded ~ $0.01) | ↓ 91.1% cheaper |
| 🥉 |
Claude Haiku 5.5
Anthropic
|
$0.008880 (rounded ~ $0.01) | ↓ 90% cheaper |
| #4 |
GPT-6 Luna
OpenAI
|
$0.008880 (rounded ~ $0.01) | ↓ 90% cheaper |
| #5 |
GPT-5.6 Luna
OpenAI
|
$0.010480 | ↓ 88.1% cheaper |
| #6 |
Gemini 3.1 Flash Lite
Google
|
$0.013100 (rounded ~ $0.01) | ↓ 85.2% cheaper |
| #7 |
Mistral Large 3
Mistral AI
|
$0.014200 (rounded ~ $0.01) | ↓ 83.9% cheaper |
| #8 |
Gemini 3.5 Flash-Lite
Google
|
$0.021320 (rounded ~ $0.02) | ↓ 75.9% cheaper |
| #9 |
Gemini 2.5 Flash
Google
|
$0.021320 (rounded ~ $0.02) | ↓ 75.9% cheaper |
| #10 |
Gemini 3.8 Flash
Google
|
$0.033300 (rounded ~ $0.03) | ↓ 62.3% cheaper |
| #11 |
Gemini 3.6 Flash
Google
|
$0.033300 (rounded ~ $0.03) | ↓ 62.3% cheaper |
| #12 |
GPT-5.4 mini
OpenAI
|
$0.039300 | ↓ 55.5% cheaper |
| #13 |
Mistral Large 4
Mistral AI
|
$0.039424 | ↓ 55.4% cheaper |
| #14 |
Claude Haiku 4.5
Anthropic
|
$0.044400 (rounded ~ $0.04) | ↓ 49.8% cheaper |
| #15 |
Gemini 3.1 Flash
Google
|
$0.052400 (rounded ~ $0.05) | ↓ 40.7% cheaper |
| #16 |
Grok 4.3
xAI
|
$0.081600 (rounded ~ $0.08) | ↓ 7.7% cheaper |
| #17 |
Grok 4.20 Beta
xAI
|
$0.081600 (rounded ~ $0.08) | ↓ 7.7% cheaper |
| #18 |
Claude Sonnet 5
Anthropic
|
$0.088800 (rounded ~ $0.09) | ↑ 0.5% more |
| #19 |
Gemini 4 Argon
Google
|
$0.088800 (rounded ~ $0.09) | ↑ 0.5% more |
| #20 |
GPT-5.6 Terra
OpenAI
|
$0.104800 (rounded ~ $0.10) | ↑ 18.6% more |
| #21 |
GPT-5.3 Codex Spark
OpenAI
|
$0.119700 | ↑ 35.4% more |
| #22 |
GPT-5.3 Instant
OpenAI
|
$0.119700 | ↑ 35.4% more |
| #23 |
Claude Sonnet 4.6
Anthropic
|
$0.133200 (rounded ~ $0.13) | ↑ 50.7% more |
| #24 |
Gemini 2.5 Pro
Google
|
$0.171000 (rounded ~ $0.17) | ↑ 93.4% more |
| #25 |
Claude Opus 5.5
Anthropic
|
$0.176800 (rounded ~ $0.18) | ↑ 100% more |
| #26 |
GPT-6.1 Sol
OpenAI
|
$0.177600 (rounded ~ $0.18) | ↑ 100.9% more |
| #27 |
GPT-6 Sol
OpenAI
|
$0.177600 (rounded ~ $0.18) | ↑ 100.9% more |
| #28 |
GPT-5.6 Sol
OpenAI
|
$0.177600 (rounded ~ $0.18) | ↑ 100.9% more |
| #29 |
Gemini 3.1 Pro
Google
|
$0.209600 | ↑ 137.1% more |
| #30 |
Claude Opus 4.7
Anthropic
|
$0.222000 (rounded ~ $0.22) | ↑ 151.1% more |
| #31 |
Claude Opus 5
Anthropic
|
$0.222000 (rounded ~ $0.22) | ↑ 151.1% more |
| #32 |
Claude Opus 4.8
Anthropic
|
$0.222000 (rounded ~ $0.22) | ↑ 151.1% more |
| #33 |
Claude Opus 4.6
Anthropic
|
$0.222000 (rounded ~ $0.22) | ↑ 151.1% more |
| #34 |
GPT-5.4
OpenAI
|
$0.262000 (rounded ~ $0.26) | ↑ 196.4% more |
| #35 |
GPT-5.4 Thinking
OpenAI
|
$0.262000 (rounded ~ $0.26) | ↑ 196.4% more |
| #36 |
GPT-5.5 Instant
OpenAI
|
$0.262000 (rounded ~ $0.26) | ↑ 196.4% more |
| #37 |
Claude Fable 5.1
Anthropic
|
$0.441000 (rounded ~ $0.44) | ↑ 398.9% more |
| #38 |
Claude Mythos 5.1
Anthropic
|
$0.441000 (rounded ~ $0.44) | ↑ 398.9% more |
| #39 |
Claude Fable 5
Anthropic
|
$0.444000 (rounded ~ $0.44) | ↑ 402.3% more |
| #40 |
Claude Mythos 5
Anthropic
|
$0.444000 (rounded ~ $0.44) | ↑ 402.3% more |
| #41 |
GPT-5.5
OpenAI
|
$0.524000 (rounded ~ $0.52) | ↑ 492.8% more |
| #42 |
GPT-6 Astra
OpenAI
|
$0.888000 (rounded ~ $0.89) | ↑ 904.5% more |
| #43 |
GPT-5.2 Pro
OpenAI
|
$1.436400 (rounded ~ $1.44) | ↑ 1524.9% more |
| #44 |
GPT-5.2 Pro
OpenAI
|
$1.436400 (rounded ~ $1.44) | ↑ 1524.9% more |
Ministral 3 (14B) Mistral AI
Nemotron 3 Super NVIDIA
Claude Haiku 5.5 Anthropic
GPT-6 Luna OpenAI
GPT-5.6 Luna OpenAI
Gemini 3.1 Flash Lite Google
Mistral Large 3 Mistral AI
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
GPT-5.4 mini OpenAI
Mistral Large 4 Mistral AI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
Grok 4.3 xAI
Grok 4.20 Beta xAI
Claude Sonnet 5 Anthropic
Gemini 4 Argon Google
GPT-5.6 Terra OpenAI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 4.6 Anthropic
Gemini 2.5 Pro Google
Claude Opus 5.5 Anthropic
GPT-6.1 Sol OpenAI
GPT-6 Sol OpenAI
GPT-5.6 Sol OpenAI
Gemini 3.1 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 5 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
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
For localization managers tasked with high-volume video script production, Claude Sonnet 5.5 offers a compelling balance of speed and structural precision. When you are managing weekly pipelines—such as the 32K-token workload referenced here—the ability of a model to adhere strictly to formatting constraints is just as critical as its creative flair.
Unlike its predecessors, Sonnet 5.5 is optimized for well-scoped, repetitive tasks, making it an excellent partner for producing localized scripts that must maintain consistent brand voice across multiple languages. Its improved speed allows for rapid iteration during the review process, where small adjustments to tone or terminology are common. Localization is inherently about context, and Sonnet 5.5 shines in roles that require ‘reviser’ capabilities: ensuring that a script localized for a specific market retains the nuance of the original while adhering to the technical constraints of the intended video format.
For teams operating at a weekly scale, this model’s reliability reduces the overhead of manual QA and ensures that scripts are ready for dubbing or subtitling without extensive re-writes. When evaluating your workflow, consider how this model handles your ‘golden documents’—the approved source scripts. Its ability to maintain coherence across lengthy technical briefs without stylistic drift is a significant advantage for managing complex localization projects efficiently. By choosing a model that excels at structural adherence, you can focus human resources on high-value cultural adaptation rather than basic text correction.