Model · Qwen2.5 · September 2024 Fixture data

Qwen2.5 7B

A 7.6 billion-parameterHow many numbers the model learned during training — the usual rough measure of its size. dense model from Qwen Team (Alibaba Cloud). Dense models from 0.5B to 72B trained on 18T tokens.

Size
7.62Bdense
Memory to run
~6 GB estimatesmallest, 8K ctx
Context
128Ktokens
License
PermissiveApache License 2.0
Updated
19 Sept 2024

Where it runs

Best-fitting version on each reference system, at an 8K contextHow much text the model can consider at once, counted in tokens — roughly ¾ of a word each..

Runs well 17

Slowly (CPU or offload) 2

Too large 0

None of the reference systems.

Measured throughput

No performance measurements recorded yet.

Versions & downloads

Each version is a separate set of weights. Expand one for its downloads: quantizationStoring each of the model’s numbers with fewer bits, so the file is smaller and needs less memory. trades a little quality for a much smaller file, and the memory column adds the working memoryExtra space the model needs while it answers. It grows with the length of the conversation, on top of the file itself. a conversation needs on top.

Variant Qwen2.5 7B InstructTuned to follow instructions and hold a conversation. The usual choice. · Qwen Team (Alibaba Cloud) · 5 downloadsPermissive
Good for
ChatCodingTool useLong context
Publisher
Qwen Team (Alibaba Cloud)
License
Apache License 2.0 · commercial use allowed
Released
19 Sept 2024

Contributions are not open yet, so there is nothing here from members.

QuantizationFormatBitsDownloadMemory @ 8KPublisher
Download BF16nativesafetensors1614.2 GiB~15.7 GiB estimateQwen Team (Alibaba Cloud)Qwen/Qwen2.5-7B-Instruct
Download Q8_0legacy ggufgguf8.57.5 GiB~8.8 GiB estimateQwen Team (Alibaba Cloud)Qwen/Qwen2.5-7B-Instruct-GGUF
Download Q4_K_Mk quantgguf4.894.3 GiB~5.4 GiB estimateQwen Team (Alibaba Cloud)Qwen/Qwen2.5-7B-Instruct-GGUF
Download AWQ 4-bitawqsafetensors4.64.1 GiB~5.2 GiB estimateQwen Team (Alibaba Cloud)Qwen/Qwen2.5-7B-Instruct-AWQ
Download MLX 4-bitmlxmlx4.54.0 GiB~5.1 GiB estimateMLX Communitymlx-community/Qwen2.5-7B-Instruct-4bit

Other sizes in Qwen2.5: Qwen2.5 14B, Qwen2.5 32B

Benchmarks

Each benchmarkA fixed set of questions every model is given, so their scores can be compared on the same task. score is labelled with who produced it. Developer-reported scores use each lab’s own prompts and settings; a benchmark that runs every model itself uses one setup for all. Bars are relative to the best open result.

BenchmarkQwen2.5 7B Instruct
Benchmark GPQA DiamondAccuracy
36.4src
Benchmark HumanEvalpass@1
84.8src
Benchmark MMLU-ProAccuracy
56.3src

developer-reported

Community

Benchmark runs and reviews from people running it on their own hardware.

Benchmark runs

Contributions are not open yet, so there is nothing here from members.

Reviews

Contributions are not open yet, so there is nothing here from members.

Details & sources

Architecture

Parameters
7.62B
Active / token
All (dense)
Architecture
Dense
Layers
28
Attention heads
28
KV heads
4
Head dim
128
KV cache @ 8K (fp16)
0.44 GiB
Max context
131,072 tokens

Lineage

How this model’s versions relate to each other and to other models.

VariantQwen2.5 7B Instruct instruct

Sources

  • Mutinai illustrative fixtures (illustrative fixture, 1 record, 13 Sept 2026)

External identifiers

Timeline

  1. Qwen2.5 family released