// head_to_head

Qwen2.5 Coder 32B Instruct vs Qwen3.6 27B

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Qwen2.5 Coder 32B Instruct is the cheaper of the two; neither can be ranked on quality here.

Qwen2.5 Coder 32B Instruct does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

qwen

Qwen2.5 Coder 32B Instruct

Blended / 1M
$0.745
Context
33K
Released
Nov 11, 2024
Overall score
Not evaluated

qwen

Qwen3.6 27B

Blended / 1M
$0.915
Context
262K
Released
Apr 27, 2026
Overall score
64.0
reasoningtool callingimage inputvideo inputprompt caching

Specs and pricing

MetricQwen2.5 Coder 32B InstructQwen3.6 27B
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

64.0
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.1074
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$0.745win$0.915
Input price / 1M$0.660$0.320win
Output price / 1M$1.00win$2.70
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.150
Context window33K262Kwin
Max output tokens29K262Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Qwen2.5 Coder 32B Instruct on top, Qwen3.6 27B below, both out of 100.

Agentic coding
39.3
Coding
71.8
Reasoning
70.3
Mathematics
79.9
Data analysis
70.4
Language
63.3
Instruction following
53.2

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadQwen2.5 Coder 32B InstructQwen3.6 27B
Support chatbot

1.2K in / 400 out × 200K requests

$238.40/mo$280.56/mo
RAG assistant

8K in / 600 out × 100K requests

$588.00/mo$350.00/mo
Coding agent

40K in / 4K out × 20K requests

$608.00/mo$376.80/mo
Document extraction

20K in / 1.5K out × 50K requests

$735.00/mo$514.00/mo
Bulk classification

500 in / 20 out × 5M requests

$1,750/mo$985.00/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Qwen3.6 27B

Wider context window — 262K against 33K.

You are cost-constrained

Qwen2.5 Coder 32B Instruct

Cheaper on blended list price at $0.745 per million tokens.

Qwen2.5 Coder 32B Instruct vs Qwen3.6 27B FAQ

Which is better, Qwen2.5 Coder 32B Instruct or Qwen3.6 27B?

Qwen2.5 Coder 32B Instruct is the cheaper of the two; neither can be ranked on quality here. Qwen2.5 Coder 32B Instruct does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Qwen2.5 Coder 32B Instruct cheaper than Qwen3.6 27B?

Qwen2.5 Coder 32B Instruct is cheaper. On a 3:1 input:output blend, Qwen2.5 Coder 32B Instruct lists at $0.745 per million tokens and Qwen3.6 27B at $0.915 — Qwen2.5 Coder 32B Instruct is 23% cheaper. Input and output are priced separately — Qwen2.5 Coder 32B Instruct charges $0.660 in and $1.00 out, Qwen3.6 27B charges $0.320 and $2.70 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Qwen2.5 Coder 32B Instruct or Qwen3.6 27B have a bigger context window?

Qwen3.6 27B has the larger context window: 33K for Qwen2.5 Coder 32B Instruct against 262K for Qwen3.6 27B. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Qwen2.5 Coder 32B Instruct and Qwen3.6 27B support prompt caching?

Qwen3.6 27B publishes a cached-input rate of $0.150 per million tokens against a full input rate of $0.320. The catalogue lists no separate cached rate for Qwen2.5 Coder 32B Instruct, which means the provider does not price it separately here — not that caching is unavailable.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • ScoresLiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.