Compare/Qwen2.5 Turbo vs gpt-oss-20B (high)

Qwen2.5 Turbovsgpt-oss-20B (high)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

Qwen2.5 Turbo

Input
$0.05/M
Output
$0.2/M
Speed
68 tok/s
TTFT
1.06s
OpenAI

gpt-oss-20B (high)

Input
$0.06/M
Output
$0.2/M
Speed
316 tok/s
TTFT
0.41s

Winner by Category

Cheaper
Qwen2.5 Turbo
Faster (tok/s)
gpt-oss-20B (high)
Lower Latency
gpt-oss-20B (high)
Benchmarks (1-11)
gpt-oss-20B (high)

Pricing Comparison

MetricQwen2.5 Turbogpt-oss-20B (high)
Input ($/M tokens)$0.05$0.06
Output ($/M tokens)$0.2$0.2
Cost for 1M input + 100K output tokens:
Qwen2.5 Turbo$0.07
gpt-oss-20B (high)$0.08

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen2.5 Turbo
68 tok/s
gpt-oss-20B (high)
316 tok/s
Time to First Token (seconds) — lower is better
Qwen2.5 Turbo
1.06s
gpt-oss-20B (high)
0.41s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
12.024.5
Coding Index
18.5
Math Index
89.3
GPQA Diamond
41.0%68.8%
MMLU-Pro
63.3%74.8%
LiveCodeBench
16.3%77.7%
AIME 2025
89.3%
MATH-500
80.5%
Humanity's Last Exam
4.2%9.8%
SciCode
15.3%34.4%
IFBench
65.1%
TerminalBench
10.6%
Qwen2.5 Turbo1 wins
11 winsgpt-oss-20B (high)

Frequently Asked Questions

Which is cheaper, Qwen2.5 Turbo or gpt-oss-20B (high)?

Qwen2.5 Turbo is cheaper overall. Its blended price (3:1 input/output ratio) is $0.09/M tokens vs $0.09/M for gpt-oss-20B (high).

Which model performs better on benchmarks?

gpt-oss-20B (high) wins 11 out of 12 benchmarks compared to 1 for Qwen2.5 Turbo. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

gpt-oss-20B (high) generates tokens faster at 316 tok/s vs 68 tok/s. However, gpt-oss-20B (high) has lower time-to-first-token (0.41s vs 1.06s).

When should I use Qwen2.5 Turbo vs gpt-oss-20B (high)?

Choose based on your priorities: Qwen2.5 Turbo for lower cost, gpt-oss-20B (high) for stronger benchmark performance, and gpt-oss-20B (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.