Qwen2.5-VL-72B-Instruct
ovhcloud · chat model
Qwen2.5-VL-72B-Instruct is listed here as a chat model from ovhcloud. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.9100 / 1M tokens |
| Output | $0.9100 / 1M tokens |
| Embedding | $0.9100 / 1M tokens |
Token limits
Capabilities
| Capability | Supported |
|---|---|
| Vision | ✅ |
| Function calling | — |
| Parallel function calling | — |
| Tool choice | — |
| Prompt caching | — |
| Reasoning | — |
| Response schema | ✅ |
| System messages | — |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| MMLU | 74.2% | accuracy | Base model: Qwen2.5 (Qwen2.5-7B-Instruct) | 2026-05-31 | Link |
| MMLU | 83.3% | accuracy | Base model: Qwen2.5 (Qwen2.5-32B-Instruct) | 2026-05-31 | Link |
| MATH | 49.8% | accuracy | Base model: Qwen2.5 (Qwen2.5-7B-Instruct) | 2026-05-31 | Link |
| MATH | 57.7% | accuracy | Base model: Qwen2.5 (Qwen2.5-32B-Instruct) | 2026-05-31 | Link |
| HumanEval | 57.9% | pass@1 | Base model: Qwen2.5 (Qwen2.5-7B-Instruct) | 2026-05-31 | Link |
| HumanEval | 58.5% | pass@1 | Base model: Qwen2.5 (Qwen2.5-32B-Instruct) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 11.9 | score | Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) | 2026-05-31 | Link |
| GPQA Diamond | 49.1% | accuracy | Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) | 2026-05-31 | Link |
| Humanity's Last Exam | 4.2% | accuracy | Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) | 2026-05-31 | Link |
| IFBench | 36.9% | accuracy | Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) | 2026-05-31 | Link |
| SciCode | 26.7% | accuracy | Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) | 2026-05-31 | Link |
| MMMU | 70 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| MMMU-Pro | 49.5 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| MMStar | 69.5 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| MathVista | 74.7 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| MathVision | 40.0 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| CC-OCR | 77.1 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| DocVQA | 94.8 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
| InfoVQA | 83.4 | score | Base model: Qwen2.5-VL (Qwen2.5-VL-32B) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Docs
| Official docs |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| Qwen2.5-VL-72B-Instruct ovhcloud | In $0.9100 / 1M tokens Out $0.9100 / 1M tokens |
Output: unknown | VisionResponse schema | 32.0K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| llama-v3p2-90b-vision-instruct fireworks_ai | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens | imagetext
Output: text | VisionResponse schema | 16.4K | Partial I/O overlap Overall 52% |
| qwen2-72b-instruct fireworks_ai | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens | text
Output: text | Response schema | 32.8K | Partial I/O overlap Overall 47% |
| Qwen2.5-Coder-32B-Instruct ovhcloud | In $0.8700 / 1M tokens Out $0.8700 / 1M tokens |
Output: unknown | Response schema | 32.0K | Same provider Overall 47% |
| llava-v1.6-mistral-7b-hf ovhcloud | In $0.2900 / 1M tokens Out $0.2900 / 1M tokens |
Output: unknown | VisionResponse schema | 32.0K | Same provider Overall 46% |
| Mixtral-8x7B-Instruct-v0.1 ovhcloud | In $0.6300 / 1M tokens Out $0.6300 / 1M tokens |
Output: unknown | Response schema | 32.0K | Same provider Overall 41% |
| qwen2.5-vl-72b-instruct novita | In $0.8000 / 1M tokens Out $0.8000 / 1M tokens | imagetext
Output: text | Vision | 32.8K | Partial I/O overlap Overall 41% |
| llama-v3p2-11b-vision-instruct fireworks_ai | In $0.2000 / 1M tokens Out $0.2000 / 1M tokens | imagetext
Output: text | VisionResponse schema | 16.4K | Partial I/O overlap Overall 37% |
| deepseek-v3 fireworks_ai | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens | text
Output: text | Response schema | 8.2K | Partial I/O overlap Overall 36% |
| deepseek-v3-0324 fireworks_ai | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens | text
Output: text | Response schema | 163.8K | Partial I/O overlap Overall 35% |
| google.gemini-2.5-flash oci | In $0.1500 / 1M tokens Out $0.6000 / 1M tokens |
Output: unknown | VisionResponse schema | 65.5K | Partial I/O overlap Overall 33% |
| nova-pro vercel_ai_gateway | In $0.8000 / 1M tokens Out $3.2000 / 1M tokens | imagetext
Output: text | VisionResponse schema | 8.2K | Partial I/O overlap Overall 32% |
| google.gemini-2.5-pro oci | In $1.2500 / 1M tokens Out $10.0000 / 1M tokens |
Output: unknown | VisionResponse schema | 65.5K | Partial I/O overlap Overall 32% |
| firefunction-v2 fireworks_ai | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens | text
Output: text | Response schema | 8.2K | Partial I/O overlap Overall 30% |
| llava-7b llamagate | In $0.1000 / 1M tokens Out $0.2000 / 1M tokens |
Output: unknown | VisionResponse schema | 2.0K | Partial I/O overlap Overall 29% |
| Mixtral-8x22B-Instruct-v0.1 anyscale | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens |
Output: unknown | Low overlap | 65.5K | Partial I/O overlap Overall 27% |
| Meta-Llama-3_3-70B-Instruct ovhcloud | In $0.6700 / 1M tokens Out $0.6700 / 1M tokens |
Output: unknown | Response schema | 131.0K | Same provider Overall 25% |
| Qwen3-32B ovhcloud | In $0.0800 / 1M tokens Out $0.2300 / 1M tokens |
Output: unknown | Response schema | 32.0K | Same provider Overall 24% |
| DeepSeek-R1-Distill-Llama-70B ovhcloud | In $0.6700 / 1M tokens Out $0.6700 / 1M tokens |
Output: unknown | Response schema | 131.0K | Same provider Overall 23% |
No models match this filter.