DeepSeek R1 vs Qwen3.5-9B
Complete pricing and performance comparison between DeepSeek's DeepSeek R1 and Alibaba's Qwen3.5-9B.
Quick Verdict
Cheaper
Qwen3.5-9B
27.0x cheaper input, 36.0x cheaper output
Larger Context
Qwen3.5-9B
262K vs 128K
Pricing Comparison
| Spec | DeepSeek R1 | Qwen3.5-9B | Difference |
|---|---|---|---|
| Provider | DeepSeek | Alibaba | |
| Input / 1M tokens | $1.35 | $0.05 | Qwen3.5-9B is 96% more expensive |
| Output / 1M tokens | $5.4 | $0.15 | Qwen3.5-9B is 97% more expensive |
| Context Window | 128K | 262K | 2x difference |
| Max Output | 33K | 33K |
Performance Benchmarks
| Metric | DeepSeek R1 | Qwen3.5-9B | Winner |
|---|---|---|---|
| Quality Index | 27 | -- | N/A |
| Value (Quality/$) | 20.1 | -- | 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 R1 | Qwen3.5-9B | Savings |
|---|---|---|---|
Single request 1K in / 300 out | $0.0030 | $0.0001 | Qwen3.5-9B saves $0.0029 |
10 requests 10K in / 3K out | $0.030 | $0.0009 | Qwen3.5-9B saves $0.029 |
100 requests 100K in / 30K out | $0.297 | $0.0095 | Qwen3.5-9B saves $0.288 |
1,000 requests 1M in / 300K out | $2.97 | $0.095 | Qwen3.5-9B saves $2.88 |
10,000 requests 10M in / 3M out | $29.70 | $0.950 | Qwen3.5-9B saves $28.75 |
1M requests/mo 1B in / 300M out | $2970.00 | $95.00 | Qwen3.5-9B saves $2875.00 |
Pros & Cons
DeepSeek R1 Strengths
Part of the DeepSeek ecosystem
Qwen3.5-9B Strengths
- +Cheaper input tokens
- +Cheaper output tokens
- +Larger context window (262K vs 128K)
When to Use Each Model
Choose DeepSeek R1 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
Frequently Asked Questions
Which is cheaper, DeepSeek R1 or Qwen3.5-9B?
For input tokens, Qwen3.5-9B is 27.0x cheaper at $0.05/1M tokens. For output tokens, Qwen3.5-9B is 36.0x cheaper at $0.15/1M tokens. At typical usage (1M input + 300K output), DeepSeek R1 costs $2.97 vs Qwen3.5-9B at $0.095.
What's the context window difference?
DeepSeek R1 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 R1 over Qwen3.5-9B?
Choose DeepSeek R1 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).
How much would 10,000 API requests cost?
At 1K input + 300 output tokens per request (typical chat): DeepSeek R1 = $29.70, Qwen3.5-9B = $0.950. At 10K input + 1K output per request (longer conversations): DeepSeek R1 = $189.00, Qwen3.5-9B = $6.50.
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