Compare/Grok 4.20 0309 v2 (Non-reasoning) vs Ling-2.6-1T

Grok 4.20 0309 v2 (Non-reasoning)vsLing-2.6-1T

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

SpaceXAI

Grok 4.20 0309 v2 (Non-reasoning)

Input
$1.25/M
Output
$2.5/M
Speed
93 tok/s
TTFT
0.66s
InclusionAI

Ling-2.6-1T

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

Winner by Category

Cheaper
Ling-2.6-1T
Faster (tok/s)
Grok 4.20 0309 v2 (Non-reasoning)
Lower Latency
Grok 4.20 0309 v2 (Non-reasoning)
Benchmarks (0-1)
Ling-2.6-1T

Pricing Comparison

MetricGrok 4.20 0309 v2 (Non-reasoning)Ling-2.6-1T
Input ($/M tokens)$1.25$0.3
Output ($/M tokens)$2.5$2.5
Cost for 1M input + 100K output tokens:
Grok 4.20 0309 v2 (Non-reasoning)$1.50
Ling-2.6-1T$0.55

Speed Comparison

Output Speed (tokens/s) — higher is better
Grok 4.20 0309 v2 (Non-reasoning)
93 tok/s
Ling-2.6-1T
Time to First Token (seconds) — lower is better
Grok 4.20 0309 v2 (Non-reasoning)
0.66s
Ling-2.6-1T

Editorial Analysis

Verdict. Ling-2.6-1T takes the aggregate benchmark matchup 1–0 across 1 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

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. Grok 4.20 0309 v2 (Non-reasoning) is strongest on Intelligence Index (22.2). Ling-2.6-1T leads on Intelligence Index (26.6).

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

Provider. SpaceXAI and InclusionAI sell to overlapping but distinct developer audiences: SpaceXAI 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): Grok 4.20 0309 v2 (Non-reasoning) costs $75.00 ($900/year); Ling-2.6-1T costs $46.50 ($558/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Grok 4.20 0309 v2 (Non-reasoning) ≈ $11.25/run, Ling-2.6-1T ≈ $6.50/run. At agent/realtime scale (200M input / 100M output per million requests): Grok 4.20 0309 v2 (Non-reasoning) ≈ $500/run, Ling-2.6-1T ≈ $310/run. Ling-2.6-1T 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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
22.226.6
Coding Index
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Grok 4.20 0309 v2 (Non-reasoning)0 wins
1 winsLing-2.6-1T

Frequently Asked Questions

Which is cheaper, Grok 4.20 0309 v2 (Non-reasoning) or Ling-2.6-1T?

Ling-2.6-1T is cheaper overall. Its blended price (3:1 input/output ratio) is $0.85/M tokens vs $1.56/M for Grok 4.20 0309 v2 (Non-reasoning).

Which model performs better on benchmarks?

Ling-2.6-1T wins 1 out of 12 benchmarks compared to 0 for Grok 4.20 0309 v2 (Non-reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Grok 4.20 0309 v2 (Non-reasoning) generates tokens faster at 93 tok/s vs — tok/s. Grok 4.20 0309 v2 (Non-reasoning) also has lower time-to-first-token (0.66s vs —s).

When should I use Grok 4.20 0309 v2 (Non-reasoning) vs Ling-2.6-1T?

Choose based on your priorities: Ling-2.6-1T for lower cost, Ling-2.6-1T for stronger benchmark performance, and Grok 4.20 0309 v2 (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.