Ling 3.0 Flash Fin
by Inclusionai · inclusionai/ling-3.0-flash-fin · #34 cheapest of 422 paid models
Prices updated Sep 19, 2026, 6:21 PM UTC · refreshed hourly
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment...
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5GPT-5.6 Sol
Pricing
Input
$0.06
per 1M tokens
Output
$0.18
per 1M tokens
Blended (3:1)
$0.09
3 input : 1 output
Cache read
$0.012
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for Ling 3.0 Flash Fin with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.09 | $0.0063 | — |
| 50% | $0.072 | $0.0039 | −38% |
| 90% | $0.058 | $0.00198 | −69% |
*Example: 100K sticky context + 2K new input + 1K output. Batch discount is an approximate 50% off list rates (available for OpenAI / Anthropic / Google — not flagged for this creator). Confirm on the vendor’s pricing page.
What a request costs
| Workload | Input tokens | Output tokens | Cost / request | Cost / 1K requests |
|---|---|---|---|---|
| Short chat message | 500 | 300 | $8.40e-5 | $0.084 |
| Document summary | 8,000 | 1,000 | $0.00066 | $0.66 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.00216 | $2.16 |
| Long-context analysis | 150,000 | 5,000 | $0.0099 | $9.90 |
Performance
Intelligence Index
23
AA composite quality
Coding Index
55.6
Math Index
—
Agentic Index
29.3
Output speed
161 tok/s
median
Time to first token
1.62s
median
Time to first answer
14.03s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| Humanity's Last Exam | 22.6% |
| SciCode | 42.4% |
| AA-LCR (Long Context Reasoning) | 73.7% |
| Terminal-Bench 2.1 | 62.5% |
| τ³-Bench Banking | 38.6% |
Specs
Context window
262K
tokens
Max output
236K
tokens
Input modalities
text
Tokenizer
Other