DeepSeek V3.2 vs Qwen3 Coder 480B A35B

Pricing math

Input pricing is close: DeepSeek V3.2 runs $0.2288/M provider ($0.235664/M on OpenKey after the 3% fee) versus Qwen3 Coder's $0.22/M provider ($0.2266/M on OpenKey) — a 1.04x ratio, basically a wash. The real split is completion cost: DeepSeek V3.2 charges $0.3432/M provider ($0.353496/M on OpenKey), while Qwen3 Coder charges $1.80/M provider ($1.854/M on OpenKey) — over 5x more per output token. On a concrete workload of 10M input tokens + 2M output tokens, DeepSeek V3.2 costs $2.97 total and Qwen3 Coder costs $5.80. If your workload generates a lot of code (long completions), that multiplier compounds fast. DeepSeek V3.2 also offers cache reads at $0.02288/M provider; Qwen3 Coder has no cache pricing listed.

Coding benchmarks

On Design Arena's coding-relevant categories, Qwen3 Coder posts higher win rates across the board: codecategories 61.2% (rank 54) vs DeepSeek's 49.7% (rank 48), dataviz 54.9% (rank 74) vs 48.8% (rank 48), gamedev 59% (rank 58) vs 46.7% (rank 50), uicomponent 61.5% (rank 56) vs 47.3% (rank 47), and website 61.7% (rank 55) vs 50.6% (rank 46). Note Qwen3 Coder's ranks are numerically worse despite higher win rates — the two models sit in different competitive bands on that leaderboard. DeepSeek V3.2 has two categories Qwen3 Coder doesn't compete in at all: 3d (elo 1210, rank 41) and asciiart (elo 1129, rank 42), plus a slightly better svg elo (1089, rank 54) than nothing to compare against on Qwen's side.

Context and long-document work

Qwen3 Coder's context window is 1,048,576 tokens against DeepSeek V3.2's 131,072 — a context ratio of 0.12, meaning DeepSeek holds about 12% of Qwen's window. For repo-wide refactors, multi-file diffs, or ingesting large codebases in one call, Qwen3 Coder is the only one of the two that fits the job without chunking. Max completion tokens are close (65,536 for Qwen3 Coder vs 64,000 for DeepSeek V3.2), so output length isn't the differentiator — input capacity is. If your prompts routinely exceed 130K tokens, DeepSeek V3.2 is disqualified regardless of price.

When to pick each

Pick DeepSeek V3.2 when cost per call matters and you need reasoning mode (it supports the `reasoning` and `include_reasoning` parameters; Qwen3 Coder has neither). Pick Qwen3 Coder when the task is genuinely large-context — big codebases, long agent traces, multi-document synthesis — and coding win-rate matters more than completion cost. Both support tool calling, structured outputs, and standard sampling parameters, so tool-use integration work is a non-issue either way. Both models run on OpenKey under one API key with the same flat 3% fee on provider list price, so switching between them mid-project doesn't require new credentials or billing setup.

Questions

Which model is cheaper for coding agents?

DeepSeek V3.2, mainly on output tokens: $0.3432/M provider vs Qwen3 Coder's $1.80/M. On a 10M-input/2M-output workload that's $2.97 total for DeepSeek V3.2 versus $5.80 for Qwen3 Coder — input pricing is nearly identical (1.04x ratio) so the completion price is what drives the gap.

Which has the bigger context window?

Qwen3 Coder, by a wide margin: 1,048,576 tokens versus DeepSeek V3.2's 131,072. That's roughly 8x more context, useful for large codebases or long agent sessions that DeepSeek V3.2 can't fit in one call.

Does either model support reasoning mode?

DeepSeek V3.2 does — it lists `reasoning` and `include_reasoning` as supported parameters, though it's not enabled by default. Qwen3 Coder has no reasoning parameter in its supported list, so it's a straight instruct model.

Which model scores better on coding benchmarks?

Qwen3 Coder posts higher Design Arena win rates in every shared category: codecategories 61.2% vs 49.7%, uicomponent 61.5% vs 47.3%, website 61.7% vs 50.6%. DeepSeek V3.2 only competes uniquely in 3d (rank 41) and asciiart (rank 42), categories Qwen3 Coder isn't scored in.