Public preview · figures are illustrative fixture data, attributed to their source · data to May 2025 · read-only
Model · Qwen2.5-Math · September 2024 Fixture data

Qwen2.5-Math 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). Math-specialised base and instruct models.

Size
7.62Bdense
Memory to run
~6 GBsmallest, 8K ctx
Context
4Ktokens
License
PermissiveApache License 2.0; MIT License
Updated
19 Sept 2024

Which version to use

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 12

Slowly (CPU or offload) 1

Too large 0

None of the reference systems.

Benchmarks

Each benchmarkA fixed set of questions every model is given, so their scores can be compared on the same task. is developer-reported; prompts and settings differ between labs. Bars are relative to the best open result.

BenchmarkDeepSeek-R1-Distill-Qwen-7B
Benchmark GPQA DiamondAccuracy
49.1src
Benchmark MATH-500Accuracy
92.8src

developer reported

Variants & downloads

Each variant 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-Math 7Bbase · Qwen Team (Alibaba Cloud) · 1 download · Apache License 2.0Permissive
What it is
Pretrained foundation weights — a starting point for fine-tuning, not for chat.
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~15.5 GiBQwen Team (Alibaba Cloud)Qwen/Qwen2.5-Math-7B
Variant DeepSeek-R1-Distill-Qwen-7Bdistill · DeepSeek (third-party) · 2 downloads · MIT LicensePermissive
What it is
A smaller model trained to imitate a larger one.
Publisher
DeepSeek
License
MIT License · commercial use allowed
Released
20 Jan 2025

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

QuantizationFormatBitsDownloadMemory @ 8KPublisher
Download BF16nativesafetensors1614.2 GiB~15.5 GiBDeepSeekdeepseek-ai/DeepSeek-R1-Distill-Qwen-7B
Download Q4_K_Mk quantgguf4.894.3 GiB~5.2 GiBLM Studio Communitylmstudio-community/DeepSeek-R1-Distill-Qwen-7B-GGUF
Architecture detailsLayers, attention and KV cache geometry
Parameters
7.62B
Active / token
All (dense)
Architecture
Dense
Layers
28
Attention heads
28
KV heads
4
Head dim
128
KV cache @ 8K (fp16)
0.22 GiB
Max context
4,096 tokens

Measured performance

Throughput on specific systems and runtimes, with the source of each measurement.

No performance measurements recorded yet.

Community results

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.

Lineage

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

VariantQwen2.5-Math 7B base
VariantDeepSeek-R1-Distill-Qwen-7B fine-tuned from Qwen2.5-Math 7B· distilled from DeepSeek-R1

Sources & history

Sources

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

External identifiers

Timeline

  1. Qwen2.5 family released