Compare/Gemini 3.5 Flash-Lite vs Ling-2.6-1T

Gemini 3.5 Flash-LitevsLing-2.6-1T

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

Google

Gemini 3.5 Flash-Lite

Input
$0.3/M
Output
$2.5/M
Speed
391 tok/s
TTFT
6.98s
InclusionAI

Ling-2.6-1T

Input
$0.3/M
Output
$2.5/M
Speed
TTFT

Winner by Category

Cheaper
Tie
Faster (tok/s)
Gemini 3.5 Flash-Lite
Lower Latency
Gemini 3.5 Flash-Lite
Benchmarks (2-0)
Gemini 3.5 Flash-Lite

Pricing Comparison

MetricGemini 3.5 Flash-LiteLing-2.6-1T
Input ($/M tokens)$0.3$0.3
Output ($/M tokens)$2.5$2.5
Cost for 1M input + 100K output tokens:
Gemini 3.5 Flash-Lite$0.55
Ling-2.6-1T$0.55

Speed Comparison

Output Speed (tokens/s) — higher is better
Gemini 3.5 Flash-Lite
391 tok/s
Ling-2.6-1T
Time to First Token (seconds) — lower is better
Gemini 3.5 Flash-Lite
6.98s
Ling-2.6-1T

Editorial Analysis

Verdict. Gemini 3.5 Flash-Lite wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Ling-2.6-1T is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Ling-2.6-1T makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Gemini 3.5 Flash-Lite is strongest on Coding Index (49.3), Intelligence Index (37.4). Ling-2.6-1T leads on Intelligence Index (26.6).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. Google and InclusionAI sell to overlapping but distinct developer audiences: Google tends to ship frontier reasoning models with premium positioning, while InclusionAI 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): Gemini 3.5 Flash-Lite costs $46.50 ($558/year); Ling-2.6-1T costs $46.50 ($558/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Gemini 3.5 Flash-Lite ≈ $6.50/run, Ling-2.6-1T ≈ $6.50/run. At agent/realtime scale (200M input / 100M output per million requests): Gemini 3.5 Flash-Lite ≈ $310/run, Ling-2.6-1T ≈ $310/run.

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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
37.426.6
Coding Index
49.3
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Gemini 3.5 Flash-Lite2 wins
0 winsLing-2.6-1T

Frequently Asked Questions

Which is cheaper, Gemini 3.5 Flash-Lite or Ling-2.6-1T?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

Gemini 3.5 Flash-Lite wins 2 out of 12 benchmarks compared to 0 for Ling-2.6-1T. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Gemini 3.5 Flash-Lite generates tokens faster at 391 tok/s vs — tok/s. Gemini 3.5 Flash-Lite also has lower time-to-first-token (6.98s vs —s).

When should I use Gemini 3.5 Flash-Lite vs Ling-2.6-1T?

Choose based on your priorities: both are similarly priced, Gemini 3.5 Flash-Lite for stronger benchmark performance, and Gemini 3.5 Flash-Lite for faster generation. For latency-sensitive apps, check the TTFT comparison above.