Pick two or three models and see exactly how far apart they are — price per million tokens, context window, and what each one can actually do.
| METRIC | GLM-5.3 Z.ai | Claude Sonnet 5 Anthropic | GPT-6 Sol OpenAI |
|---|---|---|---|
| Input $/1M | $1.40CHEAPEST | $2.00+43% | $2.00+43% |
| Cached input $/1M | $0.26+30% | $0.20CHEAPEST | $0.20CHEAPEST |
| Output $/1M | $4.40CHEAPEST | $10.00+127% | $10.00+127% |
| Blended $/1M (3:1) | $2.15CHEAPEST | $4.00+86% | $4.00+86% |
| Context window | 1.05M−0% | 1M−5% | 1.05MLARGEST |
| Capabilities | REASONINGTOOL USEOPEN WEIGHTS | REASONINGVISIONTOOL USE | REASONINGVISIONTOOL USE |
Percentages are relative to the “best” value in each row — cheapest price, largest context. Blended assumes a typical 3:1 input-to-output token ratio.
ReqKey gives every API key a credit balance — validate, deduct, enforce limits, and see per-consumer spend in real time.
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