Deepseek Coder 33B Instruct vs Qwen3 Next 80B A3b Instruct
On provider list prices, Deepseek Coder 33B Instruct costs $0.80 per million input tokens against $0.15 for Qwen3 Next 80B A3b Instruct: effectively level. Output is $0.80 against $1.50 (1.9x). On Allocate both bill at list plus the 7% transaction fee.
Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $705 a month on Qwen3 Next 80B A3b Instruct and $1,240 on Deepseek Coder 33B Instruct at list: a gap of $535, or 1.8x.
Qwen3 Next 80B A3b Instruct reads 256K tokens per request against 16K for Deepseek Coder 33B Instruct, 16.0x the window. That decides which one can take whole documents without splitting them.
Choose Deepseek Coder 33B Instruct for
- Training toward a model you own
Choose Qwen3 Next 80B A3b Instruct for
- The lower list price ($0.15 in / $1.50 out per M tokens)
- The longer context window (256K vs 16K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
Common questions
Which is cheaper, Deepseek Coder 33B Instruct or Qwen3 Next 80B A3b Instruct?
Qwen3 Next 80B A3b Instruct, on this workload shape. At list prices it is $0.15/$1.50 per million tokens in and out against $0.80/$0.80 for Deepseek Coder 33B Instruct. Billed on Allocate: $0.16/$1.60 against $0.86/$0.86, list plus 7%.
Which has the bigger context window?
Qwen3 Next 80B A3b Instruct: 262,144 tokens (256K) against 16,384 (16K) for Deepseek Coder 33B Instruct.
Can I fine-tune Deepseek Coder 33B Instruct or Qwen3 Next 80B A3b Instruct?
Both publish open weights (Deepseek Coder 33B Instruct: Custom license; Qwen3 Next 80B A3b Instruct: Apache 2.0), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
Run the numbers on your workload
Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.