Claude Sonnet 4.6
$969.00 / month- Input cost
- $819.00
- Output cost
- $150.00
- Per 1,000 calls
- $484.50
- Pricing profile
- standard
Source-tracked model comparison
Gemini 3.5 Flash vs Claude Sonnet 4.6: which costs less for a practical API workload?
Compare verified pricing and model limits for API pricing and workload fit across providers. The cost example uses a long-context research workload and does not assume equal model quality.
Direct cost answer: Claude Sonnet 4.6 is estimated at $969.00 per month and Gemini 3.5 Flash at $499.50 for 150,000 input tokens, 5,000 output tokens, and 2,000 monthly requests. Gemini 3.5 Flash is $469.50 lower under these assumptions. This does not identify a quality winner.
Tracked facts
Pricing and model limits
Prices are USD per 1M tokens under each model's verified default profile.
| Field | Claude Sonnet 4.6 | Gemini 3.5 Flash |
|---|---|---|
| Provider | Anthropic | |
| API model ID | claude-sonnet-4-6 | gemini-3.5-flash |
| Input / 1M | $3.00 | $1.50 |
| Cached input / 1M | $0.30 | $0.15 |
| Output / 1M | $15.00 | $9.00 |
| Context window | 1,000,000 tokens | 1,048,576 tokens |
| Maximum output | 128,000 tokens | 65,536 tokens |
| Accepted input | text, image | text |
Example workload
Long-context research cost scenario
150,000 input and 5,000 output tokens per request, 2,000 monthly requests, and 10% cached input.
Gemini 3.5 Flash
$499.50 / month- Input cost
- $409.50
- Output cost
- $90.00
- Per 1,000 calls
- $249.75
- Pricing profile
- standard
Cost result: Gemini 3.5 Flash is $469.50 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.
Questions to answer before choosing
- Which model meets the required quality threshold on representative inputs?
- How do output length, retries, and caching change the measured cost?
- Which provider and deployment path fit the team's operational requirements?
What this estimate leaves out
Models whose tracked context window is below the scenario input are excluded from the compatible-model table.
Latency, reliability, output quality, retries, regional processing, and provider-specific tool charges can change the practical decision.
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