Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Step 3.5 Flash 2603 | Ling 2.6 Flash |
|---|---|---|
| Input ($/M tokens) | $0.1 | $0.1 |
| Output ($/M tokens) | $0.3 | $0.3 |
Verdict. Step 3.5 Flash 2603 and Ling 2.6 Flash split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Ling 2.6 Flash is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Ling 2.6 Flash makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Step 3.5 Flash 2603 is strongest on Intelligence Index (26.5). Ling 2.6 Flash leads on Coding Index (25.3), Intelligence Index (14.2).
Speed. On throughput, Step 3.5 Flash 2603 generates tokens at 214 tok/s versus 104 tok/s — about 51% faster. On time-to-first-token, Ling 2.6 Flash responds in 1130ms vs 1140ms, which matters most for chat-style UIs.
Provider. StepFun and InclusionAI sell to overlapping but distinct developer audiences: StepFun 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): Step 3.5 Flash 2603 costs $7.50 ($90/year); Ling 2.6 Flash costs $7.50 ($90/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Step 3.5 Flash 2603 ≈ $1.10/run, Ling 2.6 Flash ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Step 3.5 Flash 2603 ≈ $50/run, Ling 2.6 Flash ≈ $50/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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Step 3.5 Flash 2603 generates tokens faster at 214 tok/s vs 104 tok/s. However, Ling 2.6 Flash has lower time-to-first-token (1.13s vs 1.14s).
Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and Step 3.5 Flash 2603 for faster generation. For latency-sensitive apps, check the TTFT comparison above.