LIVE
BODYBUILDER$-1000000.00▼ 5.4%
GLM-4-LONG$0.00▼ 14.1%
GEMINI-2.0-FLA$0.30▼ 20.0%
GEMINI-2.0-FLA$0.40▼ 6.6%
-CF$0.00▼ 9.7%
DEEPSEEK-V4-FL$0.28▼ 26.3%
LLAMA-4-MAVERI$0.60▼ 11.9%
GROK-4-FAST$0.50▼ 6.0%
QWEN-PLUS$0.78▼ 0.6%
MINIMAX-M2.1$0.95▲ 2.6%
MINIMAX-M2$1.00▲ 2.9%
MINIMAX-01$1.10▲ 8.0%
GPT-4.1-MINI$1.60▼ 13.7%
GROK-4-1-FAST-$0.50▲ 8.9%
GPT-4.1-MINI-2$1.60▼ 31.8%
XAI$0.00▲ 4.5%
MINIMAX-M2.7$0.00▼ 9.9%
QWEN3.5-FLASH-$0.26▼ 31.0%
GPT-4.1-NANO$0.40▼ 13.0%
GEMINI-2.5-FLA$0.40▼ 0.8%
DEEPSEEK-AI$0.00▼ 27.0%
GROK-4.1-FAST$0.50▼ 16.4%
MINIMAX-M3$1.20▼ 6.1%
GOOGLE$1.50▼ 3.4%
AUTO$0.00▲ 9.7%
GOOGLE$0.00▼ 27.8%
MINIMAX-M2.7$1.20▼ 7.2%
GOOGLE$0.00▼ 0.6%
BODYBUILDER$-1000000.00▼ 5.4%
GLM-4-LONG$0.00▼ 14.1%
GEMINI-2.0-FLA$0.30▼ 20.0%
GEMINI-2.0-FLA$0.40▼ 6.6%
-CF$0.00▼ 9.7%
DEEPSEEK-V4-FL$0.28▼ 26.3%
LLAMA-4-MAVERI$0.60▼ 11.9%
GROK-4-FAST$0.50▼ 6.0%
QWEN-PLUS$0.78▼ 0.6%
MINIMAX-M2.1$0.95▲ 2.6%
MINIMAX-M2$1.00▲ 2.9%
MINIMAX-01$1.10▲ 8.0%
GPT-4.1-MINI$1.60▼ 13.7%
GROK-4-1-FAST-$0.50▲ 8.9%
GPT-4.1-MINI-2$1.60▼ 31.8%
XAI$0.00▲ 4.5%
MINIMAX-M2.7$0.00▼ 9.9%
QWEN3.5-FLASH-$0.26▼ 31.0%
GPT-4.1-NANO$0.40▼ 13.0%
GEMINI-2.5-FLA$0.40▼ 0.8%
DEEPSEEK-AI$0.00▼ 27.0%
GROK-4.1-FAST$0.50▼ 16.4%
MINIMAX-M3$1.20▼ 6.1%
GOOGLE$1.50▼ 3.4%
AUTO$0.00▲ 9.7%
GOOGLE$0.00▼ 27.8%
MINIMAX-M2.7$1.20▼ 7.2%
GOOGLE$0.00▼ 0.6%
CNTextDEEPSEEK-V3.2- Live · updated daily

deepseek-v3.2-exp

DeepSeek
Efficiency score
89/100
+11.3%
Input price
$0.28/ 1M tokens
Output price
$0.42/ 1M tokens
Context window
131K
Throughput
143tok/s
Availability
98.3%
Cost / task
$0.001

Arena Elo 1368Human-preference rating · LMArena (shown where the model is ranked)

Capabilities

Accepts (input)
Text
Produces (output)
Text

7-day heat trend

+11.3%

Pricing breakdown

Input price
$0.28/ 1M tokens
$0.0003 / 1K
Output price
$0.42/ 1M tokens
$0.0004 / 1K
Blended price
$0.39/ 1M tokens
$0.0004 / 1K

Typical 3:1 output-to-input mix, per 1M tokens

Estimated monthly cost by workload

Chat assistant
$134.40/ mo
1K in · 400 out · 10K req/day
RAG / long context
$373.80/ mo
8K in · 600 out · 5K req/day
Agent / tool use
$352.80/ mo
3K in · 1.5K out · 8K req/day
Estimate your cost →

Market position

  • Cheaper than 25% of tracked models
  • Faster than 41% of tracked models
  • Efficiency rank: #295 of 1105

Best suited for

General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.

About deepseek-v3.2-exp

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attent...

deepseek-v3.2-exp is a Text model from DeepSeek (CN). HotON.ai tracks it at $0.28 per 1M input tokens and $0.42 per 1M output tokens, with a 131K-token context window, ~143 tokens/sec throughput and 98.3% availability. Its composite efficiency score is 89/100 at an estimated $0.001 per successful task.

Compare deepseek-v3.2-exp

DEEPSEEK-V3.2- vs -CFDEEPSEEK-V3.2- vs GRANITE-4.1-8BDEEPSEEK-V3.2- vs GRANITE-4.0-H-DEEPSEEK-V3.2- vs PHI-4-MINI-INS

Related market news

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Frequently asked questions

How much does deepseek-v3.2-exp cost per 1M tokens?+

deepseek-v3.2-exp is tracked at $0.28 per 1M input tokens and $0.42 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.39 per 1M tokens. Figures are illustrative demo data.

What is deepseek-v3.2-exp best for?+

General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.

How fast is deepseek-v3.2-exp?+

deepseek-v3.2-exp delivers about 143 tokens/sec with 98.3% tracked availability, suitable for latency-sensitive, real-time applications.

Is deepseek-v3.2-exp cheaper than other AI models?+

Within the HotON.ai tracked set, deepseek-v3.2-exp is cheaper than 25% of models on input price and ranks #295 of 1105 by overall efficiency.

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Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Speed, availability and efficiency are modeled estimates.