Which is cheaper for input tokens: Baidu: ERNIE 4.5 21B A3B Thinking or ByteDance Seed: Seed 1.6 Flash?
Baidu: ERNIE 4.5 21B A3B Thinking is cheaper or equal on input token cost by $0.00 per 1M tokens.
Head-to-Head Pricing Benchmark
Side-by-side pricing and context window comparison for production model selection.
Default Recommendation (120M input + 60M output)
Baidu: ERNIE 4.5 21B A3B Thinking is lower-cost for the default monthly workload scenario.
Adjust the workload in the calculator below to see a live recommendation for your usage.
| Metric | Baidu: ERNIE 4.5 21B A3B Thinking | ByteDance Seed: Seed 1.6 Flash |
|---|---|---|
| Developer | baidu | bytedance-seed |
| Context Window | 131,072 | 262,144 |
| Input Cost / 1M Tokens | $0.0700 | $0.0750 |
| Output Cost / 1M Tokens | $0.2800 | $0.3000 |
| Projected Monthly Cost | $25 | $27 |
| Vision | ❌ No | ✅ Yes |
| Tool Calling | ❌ No | ✅ Yes |
| Structured Output | ❌ No | ✅ Yes |
| Reasoning | ✅ Yes | ✅ Yes |
| MMLU Score | N/A | N/A |
Price History
Current Input / 1M
$0.0700
Current Output / 1M
$0.2800
Price History
Current Input / 1M
$0.0750
Current Output / 1M
$0.3000
Adjust your workload to see projected monthly costs.
Baidu: ERNIE 4.5 21B A3B Thinking
$25
per month
Lower costByteDance Seed: Seed 1.6 Flash
$27
per month
Live Recommendation
Baidu: ERNIE 4.5 21B A3B Thinking is lower-cost at 120M input + 60M output tokens/month.
Continue evaluation with more “A vs B pricing” decision pages.
Quick Compare
Select two models to see a head-to-head pricing breakdown.
Common questions for Baidu: ERNIE 4.5 21B A3B Thinking vs ByteDance Seed: Seed 1.6 Flash pricing decisions.
Baidu: ERNIE 4.5 21B A3B Thinking is cheaper or equal on input token cost by $0.00 per 1M tokens.
Baidu: ERNIE 4.5 21B A3B Thinking is cheaper or equal on output token cost by $0.02 per 1M tokens.
$1.80 difference for the default scenario (120M input + 60M output tokens/month).
Use this page to compare context window and token pricing, then open each model page to evaluate additional alternatives and monthly workload fit.