Ling-2.6-flash
by Inclusionai · inclusionai/ling-2.6-flash · #6 cheapest of 325 paid models
Prices updated Jul 22, 2026, 1:37 AM UTC · refreshed hourly
Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5GPT-5.6 Sol
Pricing
Input
$0.01
per 1M tokens
Output
$0.03
per 1M tokens
Blended (3:1)
$0.015
3 input : 1 output
Cache read
$0.0020
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for Ling-2.6-flash with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.015 | $0.00105 | — |
| 50% | $0.012 | $0.00065 | −38% |
| 90% | $0.0096 | $0.00033 | −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 | $1.40e-5 | $0.014 |
| Document summary | 8,000 | 1,000 | $0.00011 | $0.11 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.00036 | $0.36 |
| Long-context analysis | 150,000 | 5,000 | $0.00165 | $1.65 |
Performance
Intelligence Index
14.1
AA composite quality
Coding Index
25.3
Math Index
—
Agentic Index
2.3
Output speed
152 tok/s
median
Time to first token
0.62s
median
Time to first answer
0.62s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| GPQA Diamond | 59.3% |
| Humanity's Last Exam | 6.2% |
| SciCode | 27.1% |
| IFBench | 57.4% |
| AA-LCR (Long Context Reasoning) | 25.0% |
| Terminal-Bench Hard | 21.2% |
| Terminal-Bench 2.1 | 24.3% |
| τ²-Bench (Telecom) | 86.0% |
| τ³-Bench Banking | 2.9% |
Specs
Context window
262K
tokens
Max output
33K
tokens
Input modalities
text
Tokenizer
Other