per 1M tokens
deepseek-ai/DeepSeek-V3.2
deepinfra/deepseek-ai/DeepSeek-V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments.
Price
per 1M tokens
Providers
Each row is one seller. Prices are the published rate from that source. A dash means that source did not publish the amount. Sorted by a 3:1 blend of input and output.
No provider prices yet.
Monthly bill
Token models use the token counts. Image, video, and audio models use units times the flat rate.
$0.64 at list price for this workload
Cache
per 1M tokens
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.26/1M | $0.38/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.26 | $0.38 | Not published— |
| 2026-10-09 | token | $0.26 | $0.38 | Not published— |
| 2026-10-10 | token | $0.26 | $0.38 | Not published— |
| 2026-10-11 | token | $0.26 | $0.38 | Not published— |
| 2026-10-12 | token | $0.26 | $0.38 | Not published— |
| 2026-10-13 | token | $0.26 | $0.38 | Not published— |
| 2026-10-14 | token | $0.26 | $0.38 | Not published— |
| 2026-10-15 | token | $0.26 | $0.38 | Not published— |
| 2026-10-16 | token | $0.26 | $0.38 | Not published— |
| 2026-10-17 | token | $0.26 | $0.38 | Not published— |
| 2026-10-18 | token | $0.26 | $0.38 | Not published— |
| 2026-10-19 | token | $0.26 | $0.38 | Not published— |
| 2026-10-20 | token | $0.26 | $0.38 | Not published— |
| 2026-10-21 | token | $0.26 | $0.38 | Not published— |
| 2026-10-22 | token | $0.26 | $0.38 | Not published— |
| 2026-10-23 | token | $0.26 | $0.38 | Not published— |
| 2026-10-24 | token | $0.26 | $0.38 | Not published— |
| 2026-10-25 | token | $0.26 | $0.38 | Not published— |
| 2026-10-26 | token | $0.26 | $0.38 | Not published— |
| 2026-10-27 | token | $0.26 | $0.38 | Not published— |
| 2026-10-28 | token | $0.26 | $0.38 | Not published— |
| 2026-10-29 | token | $0.26 | $0.38 | Not published— |
| 2026-10-30 | token | $0.26 | $0.38 | Not published— |
Alternatives
- DeepSeek V3.2$0.26/1M · Compare
- DeepSeek V3.2 Exp$0.26/1M · Compare
- Qwen/Qwen3.5-27B$0.26/1M · Compare
- Qwen: Qwen-Plus$0.26/1M · Compare
- Qwen: Qwen3.5 Plus 2026-02-15$0.26/1M · Compare
- Qwen: Qwen3.5-122B-A10B$0.26/1M · Compare
Parameters (2)
chatprompt_cache
Call this model
OpenRouter id deepinfra/deepseek-ai/DeepSeek-V3.2. InferenceList does not send the request.
curl
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepinfra/deepseek-ai/DeepSeek-V3.2","messages":[{"role":"user","content":"Hello"}]}'
JavaScript
await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "deepinfra/deepseek-ai/DeepSeek-V3.2",
messages: [{ role: "user", content: "Hello" }],
}),
});
Python
import os, json, urllib.request
req = urllib.request.Request(
"https://openrouter.ai/api/v1/chat/completions",
data=json.dumps({"model": "deepinfra/deepseek-ai/DeepSeek-V3.2", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())