Qwen2.5 72B Instruct
Qwen · released Sep 19, 2024
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Specification
- Context window
- 33K
- Max output
- 16K
- Knowledge cutoff
- Jun 30, 2024
- Parameters
- 72.7B
- Licence
- other
- Serving providers
- 2
- Moderated
- No
- Uptime
- 99.6%
Intelligence
9.4
34th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
30 t/s
Median across providers
Latency
285ms
Time to first token
Cost per task
$0.03
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- MMLU-Pro72.0%
- GPQA Diamond49.1%
- IFBench36.9%
- τ²-bench (Telecom)34.5%
- LiveCodeBench27.6%
- SciCode26.7%
- AA-LCR (long context)20.0%
- AIME 202514.0%
- Terminal-Bench Hard4.5%
- Humanity's Last Exam3.6%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| MMLU-Pro | 72.0% |
| GPQA Diamond | 49.1% |
| IFBench | 36.9% |
| τ²-bench (Telecom) | 34.5% |
| LiveCodeBench | 27.6% |
| SciCode | 26.7% |
| AA-LCR (long context) | 20.0% |
| AIME 2025 | 14.0% |
| Terminal-Bench Hard | 4.5% |
| Humanity's Last Exam | 3.6% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Llama 4 ScoutMeta10.3
- 9.9
- R1 Distill Llama 70BDeepSeek9.8
- GPT-4.1 NanoOpenAI9.6
- Qwen2.5 72B InstructQwen9.4
- SonarPerplexity9.4
- GPT-4o (2024-08-06)OpenAI9.4
- Sonar ProPerplexity9.1
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Llama 4 Scout | 10.3 |
| Qwen3 VL 30B A3B Instruct | 9.9 |
| R1 Distill Llama 70B | 9.8 |
| GPT-4.1 Nano | 9.6 |
| Qwen2.5 72B Instruct | 9.4 |
| Sonar | 9.4 |
| GPT-4o (2024-08-06) | 9.4 |
| Sonar Pro | 9.1 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.36
- Output / 1M tokens
- $0.4
- Cached input / 1M
- Not offered
- Blended 3:1
- $0.37
One task, estimated
$0.03
- Input tokens
- 50,000
- Output tokens
- 25,000
- Profile
- Standard
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).