InclusionaiFastReleased 23 July 2026

Ling-3.0-flash pricing, context and benchmark

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

262K
Input context
33K
Output context
$0.021
Official input
$0.063
Official output
n/a
AA index

Everything that matters, in one table

Context, pricing, cache, modalities and tooling, from the model registry and Artificial Analysis.

ModelLing-3.0-flash
Model IDinclusionai/ling-3.0-flash
ProviderInclusionai
Release date23 July 2026
StatusGenerally available
Input context262,144 tokens
Output context32,768 tokens
Official input pricing$0.021 per 1M tokens
Official output pricing$0.063 per 1M tokens
Cache read pricing$0.015 per 1M tokens (80% off input)
Market input pricing$0.021 per 1M (cheapest route)
Market output pricing$0.063 per 1M (cheapest route)
Highest route pricing$0.06 in, $0.18 out per 1M
Input modalitiestext
Output modalitiestext
Reasoning controlNot exposed
Tool supportText generation only
TokenizerOther
Provider routes2 endpoints
Artificial Analysis indexNot published
Speed241 tokens/s, 7.39s to first token
Knowledge cutoffNot publicly stated

Input and output support

ModalityInputOutputBilled at
Text✓ yes✓ yes$0.021 in
Imagenononot supported
Audionononot supported
Videonononot supported
File (PDF)nononot supported

What is 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...

Ling-3.0-flash carries a 262K token window, uses the Other tokenizer and is served by Inclusionai. On Hoodgen it sits in the Fast tier of the model menu next to its siblings, so you can switch mid conversation without losing the thread.

Release and what changed from the previous version

Released23 July 2026

This is the only release of Ling-3.0-flash on OpenRouter, released 23 July 2026. The provider has not published a knowledge cutoff, so treat training data as recent but unconfirmed for very new events.

Features and capabilities

⚡
Prompt caching
Cached input costs $0.015 per million instead of $0.021, so stable prefixes get cheaper.

What can you do with Ling-3.0-flash?

High volume drafts
Captions, titles, product blurbs and rewrite passes where cost per call dominates.
Inline assistants
Autocomplete, quick replies and menu helpers that must answer inside a second.
Batch classification
Tagging, routing and extraction across thousands of short inputs.
Cheap agent loops
Tool calling loops that do not need frontier grade reasoning.

Prompt caching and how to cut the bill

Cached input bills at $0.015 per million instead of $0.021, a 80% discount. Keep the system prompt and documents first and the changing question last, so every call hits the cache.

Ling-3.0-flash pricing

Official pricing

List price
$0.021 / 1M in
$0.063 / 1M out
  • $0.015 cached input
  • 262K context
  • text input
Cheapest route
$0.021 / 1M in
$0.063 / 1M out
  • 2 routes on OpenRouter
  • What Hoodgen routes to first
  • Same model, lower bill
Highest route
$0.06 / 1M in
$0.18 / 1M out
  • Priority or premium tier
  • Best under load
  • Use for latency critical calls

Market pricing, every route

ProviderTierInputOutputCache readUptime 24h
Novitastandard$0.021$0.063$0.0042100.0%
DeepInfrastandard$0.06$0.18$0.01296.7%

API pricing and cost calculator

RatePer callTotalCredits
Cheapest route$0.0003$0.16149
List price$0.0004$0.22211
Highest route$0.0015$0.73699

API and developer information

Model IDinclusionai/ling-3.0-flash
Endpointhttps://openrouter.ai/api/v1/chat/completions
Parametersprompt and max_tokens
StreamingYes, server sent events
Modality stringtext->text
Max prompt tokens262,144
Max completion tokens32,768
curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "inclusionai/ling-3.0-flash",
    "messages": [{ "role": "user", "content": "Summarise this document." }],
    "max_tokens": 1024
  }'

Model limitations

Text only outputIt cannot generate images, audio or video. Pair it with an image model on Hoodgen when you need visuals.
Output cap32,768 tokens per request. Long deliverables have to be chunked.
Benchmarks not publishedArtificial Analysis does not publish an Intelligence Index for this release, so no benchmark score is claimed here.
Knowledge cutoffThe provider does not state a fixed cutoff for every release. Verify very recent events against search.
Depth ceilingFast tier: strong on throughput, weaker than flagship tiers on long multi step reasoning.

Ling-3.0-flash vs other Inclusionai models

ModelContextInput /1MOutput /1MAA indexReleased
Ling-3.0-flash262K$0.021$0.063n/a2026
Ling 3.1 Flash1M$0.045$0.135n/aOct 2026

Privacy and data policy

  • On Hoodgen, prompts and attachments answer that request and stay in your conversation history so you can reopen it. They are not used to train models.
  • Requests route through OpenRouter to Inclusionai and are covered by that provider's API terms.
  • Do not paste secrets or personal data you would not send to any hosted model.

Ling-3.0-flash questions, answered

Ling-3.0-flash is a fast model from Inclusionai, released 23 July 2026. *Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*.
✦

Start chatting with Ling-3.0-flash

Free to try on Hoodgen AI, with a live credit estimate before every send. No API key, no setup.