DeepSeek V3.2 (Chat) vs Qwen3.5-9B
Complete pricing and performance comparison between DeepSeek's DeepSeek V3.2 (Chat) and Alibaba's Qwen3.5-9B.
Quick Verdict
Cheaper
Qwen3.5-9B
5.6x cheaper input, 2.8x cheaper output
Larger Context
Qwen3.5-9B
262K vs 128K
Pricing Comparison
| Spec | DeepSeek V3.2 (Chat) | Qwen3.5-9B | Difference |
|---|---|---|---|
| Provider | DeepSeek | Alibaba | |
| Input / 1M tokens | $0.28 | $0.05 | Qwen3.5-9B is 82% more expensive |
| Output / 1M tokens | $0.42 | $0.15 | Qwen3.5-9B is 64% more expensive |
| Context Window | 128K | 262K | 2x difference |
| Max Output | 8K | 33K |
Performance Benchmarks
| Metric | DeepSeek V3.2 (Chat) | Qwen3.5-9B | Winner |
|---|---|---|---|
| Quality Index | 32 | -- | N/A |
| Output Speed | 34 tok/s | -- | N/A |
| Value (Quality/$) | 114.6 | -- | Higher = better value |
Benchmark data from Artificial Analysis. Quality Index is a composite score across reasoning, coding, and knowledge tasks.
Cost at Scale
Estimated cost at different usage levels (3:1 input-to-output token ratio, typical for chat).
| Usage | DeepSeek V3.2 (Chat) | Qwen3.5-9B | Savings |
|---|---|---|---|
Single request 1K in / 300 out | $0.0004 | $0.0001 | Same |
10 requests 10K in / 3K out | $0.0041 | $0.0009 | Qwen3.5-9B saves $0.0031 |
100 requests 100K in / 30K out | $0.041 | $0.0095 | Qwen3.5-9B saves $0.031 |
1,000 requests 1M in / 300K out | $0.406 | $0.095 | Qwen3.5-9B saves $0.311 |
10,000 requests 10M in / 3M out | $4.06 | $0.950 | Qwen3.5-9B saves $3.11 |
1M requests/mo 1B in / 300M out | $406.00 | $95.00 | Qwen3.5-9B saves $311.00 |
Pros & Cons
DeepSeek V3.2 (Chat) Strengths
Part of the DeepSeek ecosystem
Qwen3.5-9B Strengths
- +Cheaper input tokens
- +Cheaper output tokens
- +Larger context window (262K vs 128K)
- +Higher max output tokens
When to Use Each Model
Choose DeepSeek V3.2 (Chat) for
- →Projects already integrated with DeepSeek's ecosystem
Choose Qwen3.5-9B for
- →Budget-conscious projects where cost is the primary factor
- →Long documents, large codebases, or multi-turn conversations
- →Generating long-form content or detailed code
Frequently Asked Questions
Which is cheaper, DeepSeek V3.2 (Chat) or Qwen3.5-9B?
For input tokens, Qwen3.5-9B is 5.6x cheaper at $0.05/1M tokens. For output tokens, Qwen3.5-9B is 2.8x cheaper at $0.15/1M tokens. At typical usage (1M input + 300K output), DeepSeek V3.2 (Chat) costs $0.406 vs Qwen3.5-9B at $0.095.
What's the context window difference?
DeepSeek V3.2 (Chat) supports 128K context (128,000 tokens), while Qwen3.5-9B supports 262K (262,144 tokens). Qwen3.5-9B can handle 2x more context in a single request.
Which model has better benchmarks?
When should I choose DeepSeek V3.2 (Chat) over Qwen3.5-9B?
Choose DeepSeek V3.2 (Chat) when you need: a DeepSeek ecosystem model. Choose Qwen3.5-9B when you need: Cheaper input tokens, Cheaper output tokens, Larger context window (262K vs 128K), Higher max output tokens.
How much would 10,000 API requests cost?
At 1K input + 300 output tokens per request (typical chat): DeepSeek V3.2 (Chat) = $4.06, Qwen3.5-9B = $0.950. At 10K input + 1K output per request (longer conversations): DeepSeek V3.2 (Chat) = $32.20, Qwen3.5-9B = $6.50.
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