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inclusionAI: Ling 3.0 Flash

Ling-3.0-flash is a 124B-parameter Mixture-of-Experts (MoE) model, with approximately 5.1B parameters activated per token.

The model is designed with token efficiency and production-scale agentic inference as key priorities, enabling developers to complete more useful work within constrained token, latency, and serving-cost budgets.

Modalities
In / out price
65% off
$0.021 / $0.063per 1M
Context
262K
Released
Jul 23, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input
$0.01346/M tokens
Output
$0.08211/M tokens
Price history
No effective price data for this selection

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput
73tok/s

P50, best across providers

Latency
0.54s

P50, best provider

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)The model was reachable. Request routed to a provider.
100.00%
Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.
99.92%

Availability over the last 3 days

Last 72 hours
Availability 99.92%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.93%
Without Routing
99.62%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for inclusionAI: Ling 3.0 Flash (Artificial Analysis)
SourceBenchmarkScore
Artificial AnalysisLing 3.0 Flash Coding Index50.6
Artificial AnalysisLing 3.0 Flash Agentic Index19.3
Artificial AnalysisLing 3.0 Flash GPQA Diamond85.5%
Artificial AnalysisLing 3.0 Flash HLE23.7%
Artificial AnalysisLing 3.0 Flash AA-LCR73.0%
Artificial AnalysisLing 3.0 Flash τ-Bench Banking27.2%
Artificial AnalysisLing 3.0 Flash GDPval-AA22.8%
Artificial AnalysisLing 3.0 Flash CritPt1.7%
Artificial AnalysisLing 3.0 Flash SciCode42.0%
Artificial AnalysisLing 3.0 Flash Terminal-Bench 4.00.0%
Artificial AnalysisLing 3.0 Flash Terminal-Bench 2.155.4%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

1.
Favicon for https://nousresearch.com
Hermes Agent
51.4Btokens
2.
51.1Btokens
3.
38.9Btokens
4.
14.5Btokens
5.
Favicon for https://github.com/thedotmack/claude-mem
claude-mem
11.8Btokens
Rest of OpenRouter
3.18B
Top 5 Apps
2.53B

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Not currently available through EU in-region routing. In-region routing docs

Frequently asked questions

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