Claude Opus 4.8
$1,615.00 / month- Input cost
- $1,365.00
- Output cost
- $250.00
- Per 1,000 calls
- $807.50
- Pricing profile
- standard
Source-tracked model comparison
Claude Opus 4.8 vs Gemini 3.1 Pro Preview: how do research-workload costs compare?
Compare verified pricing and model limits for premium long-context research across Anthropic and Google. The cost example uses a long-context research workload and does not assume equal model quality.
Direct cost answer: Claude Opus 4.8 is estimated at $1,615.00 per month and Gemini 3.1 Pro Preview at $666.00 for 150,000 input tokens, 5,000 output tokens, and 2,000 monthly requests. Gemini 3.1 Pro Preview is $949.00 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 Opus 4.8 | Gemini 3.1 Pro Preview |
|---|---|---|
| Provider | Anthropic | |
| API model ID | claude-opus-4-8 | gemini-3.1-pro-preview |
| Input / 1M | $5.00 | $2.00 |
| Cached input / 1M | $0.50 | $0.20 |
| Output / 1M | $25.00 | $12.00 |
| 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 3.1 Pro Preview
$666.00 / month- Input cost
- $546.00
- Output cost
- $120.00
- Per 1,000 calls
- $333.00
- Pricing profile
- standard
Cost result: Gemini 3.1 Pro Preview is $949.00 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.
Questions to answer before choosing
- Which model preserves the required source details?
- Does either input cross a tracked pricing threshold?
- How does preview availability affect production use?
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.