Qwen2.5-14B-Instruct-1M

Language Alibaba Qwen Partly verified Released Jan 27, 2025
  • Tool use
  • Structured output
  • Open weights

Prices

1 offering · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official Global · USD qwen2.5-14b-instruct-1m
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 1, 2026 past price, from the vendor’s page archived Jan 16, 2026$0.805$3.22

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Sep 30, 2026)

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

Details

Reasoning
—
Family
qwen
Model ID

Not stated on Alibaba Qwen’s pages: max input, input modalities, output modalities, reasoning efforts, reasoning can be off, max thinking budget, built-in tools, knowledge cutoff, licence, aliases.

Run locally

Weights: Qwen/Qwen2.5-14B-Instruct-1M
  • Parameters 14.8B
  • Dense
  • Native precision BF16
  • Layers 48
  • KV cache per token 192 KB
  • Config positions 986K (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
Runs well Q8_0 (automatic) 8K context 29–44 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 16.8 GB (weights 14.6 + KV cache 1.5 + overhead 0.7)
Usable
21.6 GB (90% of its memory)
Generation speed
29–44 tok/s
Longest context
33K (longer doesn’t fit)
First token
about 0.48–0.72 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file27.5 GB≈ 30.4Needs system memory 4–6 tok/s—
Q8_014.6 GB≈ 16.8Runs well 29–44 tok/s33K
FP813.8 GB≈ 15.9Runs well 31–46 tok/s38K
Q6_K11.3 GB≈ 13.4Runs well 37–55 tok/s51K
Q5_K_M9.8 GB≈ 11.8Runs well 42–62 tok/s60K
Q5_09.5 GB≈ 11.5Runs well 43–64 tok/s62K
Q4_K_M8.4 GB≈ 10.4Runs well 48–71 tok/s68K
Q4_07.7 GB≈ 9.7Runs well 51–76 tok/s71K
IQ4_XS7.3 GB≈ 9.3Runs well 53–80 tok/s73K
Q3_K_Mquality drops6.7 GB≈ 8.7Runs well 57–86 tok/s76K
IQ3_XXSquality drops5.3 GB≈ 7.3Runs well 69–104 tok/s84K
Q2_Kquality drops5.2 GB≈ 7.2Runs well 70–106 tok/s85K
IQ2_XXSquality drops3.5 GB≈ 5.5Runs well 93–140 tok/s93K

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): GPU GeForce RTX 5070; unified memory Apple M5 · 16 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≈ 223.0 GBDoesn’t fit your hardware
LoRA≈ 30.8 GBDoesn’t fit your hardware
QLoRA≈ 11.0 GBFits 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.

No changes recorded yet.

Sources

Alibaba Qwen’s official policies: data use, privacy, terms →

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

Alibaba Qwen · China · qwen.ai

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