Compare/Ling 3.0 Tiny vs Gemini 3.5 Flash (high)

Ling 3.0 TinyvsGemini 3.5 Flash (high)

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

InclusionAI

Ling 3.0 Tiny

Input
$0/M
Output
$0/M
Speed
175 tok/s
TTFT
2.57s
Google

Gemini 3.5 Flash (high)

Input
$1.5/M
Output
$9/M
Speed
171 tok/s
TTFT
27.29s

Winner by Category

Cheaper
Ling 3.0 Tiny
Faster (tok/s)
Ling 3.0 Tiny
Lower Latency
Ling 3.0 Tiny
Benchmarks (0-2)
Gemini 3.5 Flash (high)

Pricing Comparison

MetricLing 3.0 TinyGemini 3.5 Flash (high)
Input ($/M tokens)$0$1.5
Output ($/M tokens)$0$9
Cost for 1M input + 100K output tokens:
Ling 3.0 Tiny$0.00
Gemini 3.5 Flash (high)$2.40

Speed Comparison

Output Speed (tokens/s) — higher is better
Ling 3.0 Tiny
175 tok/s
Gemini 3.5 Flash (high)
171 tok/s
Time to First Token (seconds) — lower is better
Ling 3.0 Tiny
2.57s
Gemini 3.5 Flash (high)
27.29s

Editorial Analysis

Verdict. Gemini 3.5 Flash (high) 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. Ling 3.0 Tiny is strongest on Coding Index (26.5), Intelligence Index (24.5). Gemini 3.5 Flash (high) leads on Coding Index (70.1), Intelligence Index (52.0).

Speed. Throughput is comparable — 175 tok/s vs 171 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.

Provider. InclusionAI and Google sell to overlapping but distinct developer audiences: InclusionAI tends to ship frontier reasoning models with premium positioning, while Google 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): Ling 3.0 Tiny costs $0.00 ($0/year); Gemini 3.5 Flash (high) costs $180.00 ($2160/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Ling 3.0 Tiny ≈ $0.00/run, Gemini 3.5 Flash (high) ≈ $25.50/run. At agent/realtime scale (200M input / 100M output per million requests): Ling 3.0 Tiny ≈ $0/run, Gemini 3.5 Flash (high) ≈ $1200/run. Ling 3.0 Tiny 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

  • Time-to-first-token differs by 10.6× — Ling 3.0 Tiny responds in 2570ms vs 27290ms. For interactive chat UIs this can matter more than raw benchmark wins.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
24.552.0
Coding Index
26.570.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Ling 3.0 Tiny0 wins
2 winsGemini 3.5 Flash (high)

Frequently Asked Questions

Which is cheaper, Ling 3.0 Tiny or Gemini 3.5 Flash (high)?

Ling 3.0 Tiny is cheaper overall. Its blended price (3:1 input/output ratio) is $0.00/M tokens vs $3.38/M for Gemini 3.5 Flash (high).

Which model performs better on benchmarks?

Gemini 3.5 Flash (high) wins 2 out of 12 benchmarks compared to 0 for Ling 3.0 Tiny. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Ling 3.0 Tiny generates tokens faster at 175 tok/s vs 171 tok/s. Ling 3.0 Tiny also has lower time-to-first-token (2.57s vs 27.29s).

When should I use Ling 3.0 Tiny vs Gemini 3.5 Flash (high)?

Choose based on your priorities: Ling 3.0 Tiny for lower cost, Gemini 3.5 Flash (high) for stronger benchmark performance, and Ling 3.0 Tiny for faster generation. For latency-sensitive apps, check the TTFT comparison above.