LLM Compare
Head to head

Fish Audio Drama 3 vs Mercury 3

How Fish Audio Drama 3 and Mercury 3 stack up across benchmarks, pricing, speed, and the workloads that matter.

Fish Audio Drama 3

Fish Audio · Proprietary

Blended pricen/aper 1M tokens
Contextn/atokens
Speedn/atok/s
Benchmarks5results
VS

Mercury 3

Inception · Proprietary

Blended price$0.13per 1M tokens
Context1Mtokens
Speed1068tok/s
Benchmarks12results

On reasoning, Fish Audio Drama 3 leads by about 26 points in our normalized benchmark average.

The table below breaks down every workload axis where both models have published results. Each score is a normalized 0 to 1 average across the benchmarks tagged with that category. A gap of a few points is noise; a gap of ten or more is a real difference in capability. Where one model has not reported a result, the cell shows n/a and the missing benchmark does not drag its average down.

Benchmark scores by workload

WorkloadFish Audio Drama 3Mercury 3Edge
Reasoning 93% 67% +26.1 pts
Coding n/a 49% n/a
Agents & tool use n/a 40% n/a
Long context n/a 77% n/a
Knowledge & factuality 93% 65% +28.2 pts

The headline benchmarks below are the most widely cited individual tests. GPQA Diamond measures graduate-level reasoning in physics, chemistry, and biology. SWE-Bench Verified tests whether a model can fix real GitHub issues. MMMU-Pro covers college-level multimodal understanding across six disciplines. AIME and FrontierMath push competitive and research math. BrowseComp measures web research ability.

Headline benchmarks

BenchmarkFish Audio Drama 3Mercury 3
GPQA n/a 89%

Benchmarks tell you what a model can do in a controlled setting. They do not tell you whether it will work on your specific task, with your specific data, at your specific scale. The recommendations below map each common workload to whichever of these two models scores higher on the relevant axis. Use them as a starting point, not a final answer.

Which should you choose?

Hard reasoning

Multi-step analysis, research, and problems that need sustained thought.

Fish Audio Drama 3

Coding & software

Writing, reviewing, and debugging code across a real codebase.

Mercury 3

Agents & tool use

Long-running agents that call tools, browse, and act on their own.

Mercury 3

Long documents

Whole codebases, books, and transcripts that fill the context window.

Mercury 3

Scores are normalized from public benchmarks published by llm-stats.com and averaged per workload. Pricing is the blended input/output cost per million tokens at an 8:1 mix. Refreshes daily. How this works.