Compare/LFM2.5-8B-A1B vs Mercury 2

LFM2.5-8B-A1BvsMercury 2

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

Liquid AI

LFM2.5-8B-A1B

Input
$0/M
Output
$0/M
Speed
339 tok/s
TTFT
1.95s
Inception

Mercury 2

Input
$0.25/M
Output
$0.75/M
Speed
835 tok/s
TTFT
3.93s

Winner by Category

Cheaper
LFM2.5-8B-A1B
Faster (tok/s)
Mercury 2
Lower Latency
LFM2.5-8B-A1B
Benchmarks (0-2)
Mercury 2

Pricing Comparison

MetricLFM2.5-8B-A1BMercury 2
Input ($/M tokens)$0$0.25
Output ($/M tokens)$0$0.75
Cost for 1M input + 100K output tokens:
LFM2.5-8B-A1B$0.00
Mercury 2$0.33

Speed Comparison

Output Speed (tokens/s) — higher is better
LFM2.5-8B-A1B
339 tok/s
Mercury 2
835 tok/s
Time to First Token (seconds) — lower is better
LFM2.5-8B-A1B
1.95s
Mercury 2
3.93s

Editorial Analysis

Verdict. Mercury 2 takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

Pricing. Pricing varies significantly between these models — check the table above for the exact per-token rates. Many production workloads actually surface input-token cost (retrieval-augmented prompts, code-context windows), so factor both directions.

Strengths. LFM2.5-8B-A1B is strongest on Intelligence Index (8.1). Mercury 2 leads on Coding Index (31.1), Intelligence Index (21.9).

Speed. On throughput, Mercury 2 generates tokens at 835 tok/s versus 339 tok/s — about 59% faster. On time-to-first-token, LFM2.5-8B-A1B responds in 1950ms vs 3930ms, which matters most for chat-style UIs.

Provider. Liquid AI and Inception sell to overlapping but distinct developer audiences: Liquid AI tends to ship frontier reasoning models with premium positioning, while Inception often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): LFM2.5-8B-A1B costs $0.00 ($0/year); Mercury 2 costs $18.75 ($225/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): LFM2.5-8B-A1B ≈ $0.00/run, Mercury 2 ≈ $2.75/run. At agent/realtime scale (200M input / 100M output per million requests): LFM2.5-8B-A1B ≈ $0/run, Mercury 2 ≈ $125/run. LFM2.5-8B-A1B becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Head-to-head deltas

  • On throughput, Mercury 2 is 2.47× faster (835 tok/s vs 339 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
8.121.9
Coding Index
31.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
LFM2.5-8B-A1B0 wins
2 winsMercury 2

Frequently Asked Questions

Which is cheaper, LFM2.5-8B-A1B or Mercury 2?

LFM2.5-8B-A1B is cheaper overall. Its blended price (3:1 input/output ratio) is $0.00/M tokens vs $0.38/M for Mercury 2.

Which model performs better on benchmarks?

Mercury 2 wins 2 out of 12 benchmarks compared to 0 for LFM2.5-8B-A1B. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Mercury 2 generates tokens faster at 835 tok/s vs 339 tok/s. LFM2.5-8B-A1B also has lower time-to-first-token (1.95s vs 3.93s).

When should I use LFM2.5-8B-A1B vs Mercury 2?

Choose based on your priorities: LFM2.5-8B-A1B for lower cost, Mercury 2 for stronger benchmark performance, and Mercury 2 for faster generation. For latency-sensitive apps, check the TTFT comparison above.