Qwen2.5 7B Instruct
Apache-2.0-licensed 7B model with surprisingly strong reasoning and multilingual chops. Qwen 2.5 trains on a larger and more carefully filtered corpus than the original Qwen series, and the 7B variant punches well above its weight on coding and math benchmarks. A strong default for cost-sensitive chat workloads and for fine-tuning experiments where the Apache licence simplifies downstream redistribution.
- Parameters
- 7B
- Context length
- 128K
- Modality
- text
- Released
- 2024-09-18
Memory & hardware
- VRAM (fp16)
- 14 GB
- VRAM (Q4)
- 4.2 GB
- Recommended
- RTX 3090 24GB
- Quantizations
- fp16, q8_0, q5_k_m, q4_k_m, gguf
Benchmarks
Hosted inference pricing
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| deepinfraCheapest | $0.08 | $0.30 |
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run qwen2.5:7b
vllm serve Qwen/Qwen2.5-7B-Instruct
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-7B-Instruct", device_map="auto", torch_dtype="auto"
)Qwen/Qwen2.5-7B-Instruct Related models
Same family or similar size — useful when shopping around.
The April 2025 refresh of Qwen at 8B. Native mixed-mode reasoning: the model can 'think' before answering when triggered, or answer directly for simple queries — configurable per request. Apache 2.0. A strong upgrade over Qwen 2.5 7B on math and code, with much better instruction following.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 4.8 GB
TII's latest dense 7B from December 2024. Strong scores on commonsense reasoning benchmarks. TII's Falcon licence permits royalty-free commercial use with attribution.
- Context
- 33K
- License
- falcon-2
- VRAM Q4
- 4.2 GB
The first major open-weights state-space model. Linear-time decoding, no KV cache — memory usage stays flat as context grows, which makes it interesting for very long-context workloads. Falcon licence.
- Context
- 16K
- License
- falcon-2
- VRAM Q4
- 4.2 GB
The original Mistral 7B refresh with 32K context and extended vocabulary. Permissive Apache 2.0 weights and the first widely-deployed sliding-window-attention model. Still useful in 2026 for very-low-cost inference and as a baseline for fine-tuning experiments.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 4.2 GB
Fully-open 7B model: weights, training data and code all released under permissive licences. Useful as a reference for reproducibility research and for teams that need full transparency on training data provenance.
- Context
- 4K
- License
- apache-2-0
- VRAM Q4
- 4.2 GB
The original 7B RLHF chat model. Historically important — the first widely-adopted commercially-usable open-weights chat model. Still cited as a baseline in most 2024–25 papers.
- Context
- 4K
- License
- llama-2
- VRAM Q4
- 4.2 GB