Ling-3.1-flash

Language Ant Group Partly verified
  • In Input modalities: Text Out Output modalities: Text
  • Reasoning
  • Reasoning can be off
  • Tool use
  • Open weights

Prices

1 offering · prices as listed
Ant Ling API (opens in a new tab) Official China · CNY Ling-3.1-flash
Conditions/ 1M tokensInputCache readOutput
Standard ¥2.00¥0.40¥6.00

Prices from Ant Ling: model pricing (opens in a new tab) (checked Nov 4, 2026)

Standard: the price a request with no conditions pays (the headline price elsewhere on the site).

Details

Licence
mit
Family
ling-flash
Model ID

Not stated on Ant Group’s pages: max input, reasoning efforts, max thinking budget, structured output, built-in tools, knowledge cutoff, aliases.

Run locally

Weights: inclusionAI/Ling-3.1-flash
  • Parameters 572.1B
  • Active 25B · 512 experts, 8 per token
  • Native precision FP8
  • Layers 72
  • KV cache per token 81 KB
  • Config positions 256K (config.json max_position_embeddings)
  • API context 977K (maker’s API)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Doesn’t fit IQ4_XS (automatic) 8K context
WeightsKV cacheOverheadUsable
Needs
≈ 297.9 GB (weights 283.1 + KV cache 0.6 + overhead 14.2)
Usable
21.6 GB (90% of its memory)
Try
it’s too large for this hardware; see the smallest that runs it below
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
FP8 (native)maker’s file534.4 GB≈ 561.7Doesn’t fit—
Q6_K437.6 GB≈ 460.1Doesn’t fit—
Q5_K_M379.0 GB≈ 398.6Doesn’t fit—
Q5_0366.3 GB≈ 385.3Doesn’t fit—
Q4_K_M323.7 GB≈ 340.5Doesn’t fit—
Q4_0299.7 GB≈ 315.3Doesn’t fit—
IQ4_XS283.1 GB≈ 297.9Doesn’t fit—
Q3_K_Mquality drops260.4 GB≈ 274.1Doesn’t fit—
IQ3_XXSquality drops203.8 GB≈ 214.6Doesn’t fit—
Q2_Kquality drops199.8 GB≈ 210.4Doesn’t fit—
IQ2_XXSquality drops137.2 GB≈ 144.7Doesn’t fit—

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): no single listed GPU; unified memory Apple M5 Ultra (80-core GPU) · 512 GB.

Run commands

The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.

Memory to fine-tune
Full≈ 8527.2 GBDoesn’t fit your hardware
LoRA≈ 1068.4 GBDoesn’t fit your hardware
QLoRA≈ 302.5 GBDoesn’t fit your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us

This model isn’t on any leaderboard we cite yet.

Price history

Ant Ling API, China · standard rate · as listed

Input per 1M tokens

0¥1.00¥2.00¥3.00Oct 9Oct 23Nov 6CNY per 1M tokensOct 15, 2026: ¥0.50Oct 28, 2026: ¥2.00Nov 6, 2026: ¥2.00
Input price history
FromPrice
Oct 9, 2026Free
Oct 15, 2026¥0.50
Oct 28, 2026¥2.00

Output per 1M tokens

0¥2.00¥4.00¥6.00¥8.00Oct 9Oct 23Nov 6CNY per 1M tokensOct 15, 2026: ¥1.50Oct 28, 2026: ¥6.00Nov 6, 2026: ¥6.00
Output price history
FromPrice
Oct 9, 2026Free
Oct 15, 2026¥1.50
Oct 28, 2026¥6.00
  1. Context window 256K → 1M
  2. Cache read price cut 20% ¥0.125 → ¥0.10 / 1M tokens · Ant Ling API, China
  3. Cache read price raised Free → ¥0.125 / 1M tokens · Ant Ling API, China
  4. Output price raised Free → ¥1.50 / 1M tokens · Ant Ling API, China
  5. Input price raised Free → ¥0.50 / 1M tokens · Ant Ling API, China
  6. New language model

Sources

Some values on this page are still waiting to be checked against official pages: a filled dot is verified, a hollow one is not yet (with or without a source on file). How we verify data

Ant Group · China · developer.ant-ling.com

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