Step 3.5 Flash vs Step 3.5 Flash 2603
Head-to-head specifications
| Metric | Step 3.5 Flash | Step 3.5 Flash 2603 | Difference |
|---|---|---|---|
| Intelligence Index | 29.0 | 29.0 | — |
| Context window | 262K tokens | 262K tokens | — |
| Blended price ($/1M tokens) | $0.12 | $0.06 | +100.0% |
| Output speed (tokens/s) | 239 | 248 | -3.6% |
| Access | Proprietary API | Proprietary API | — |
- Step 3.5 Flash leads overall capability (Intelligence Index 29.0 vs 29.0).
- Step 3.5 Flash 2603 is the cheaper model to run at $0.06/1M blended tokens — about 2.0× cheaper.
Verdict: Step 3.5 Flash or Step 3.5 Flash 2603?
Step 3.5 Flash advantages
- No decisive advantage on the tracked metrics.
Step 3.5 Flash 2603 advantages
- Affordability (+50%)
Which should you choose?
- Choose the Step 3.5 Flash 2603 if you want the lowest cost per token at scale.
Value for money
Step 3.5 Flash 2603 offers more intelligence per dollar (2.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Step 3.5 Flash vs Step 3.5 Flash 2603: which should you choose?
Step 3.5 Flash — StepFun multimodal model with an Intelligence Index of 29, a 262K-token context window and a blended price of $0.12/1M tokens.
Step 3.5 Flash 2603 — StepFun multimodal model with an Intelligence Index of 29, a 262K-token context window and a blended price of $0.06/1M tokens.
Step 3.5 Flash vs Step 3.5 Flash 2603: Step 3.5 Flash scores higher on the Intelligence Index. Step 3.5 Flash leads overall capability (Intelligence Index 29.0 vs 29.0). Step 3.5 Flash 2603 is the cheaper model to run at $0.06/1M blended tokens — about 2.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Step 3.5 Flash scores 29.0 versus 29.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Step 3.5 Flash accepts up to 262K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Step 3.5 Flash 2603 generates faster (248 vs 239 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Step 3.5 Flash 2603 is the cheaper model to run ($0.06 vs $0.12 per 1M tokens). Step 3.5 Flash is proprietary api and Step 3.5 Flash 2603 is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Step 3.5 Flash better than the Step 3.5 Flash 2603?
Step 3.5 Flash 2603 is the clearly stronger overall choice, winning most of the dimensions that matter. Step 3.5 Flash leads overall capability (Intelligence Index 29.0 vs 29.0).
What is the main difference between the Step 3.5 Flash and the Step 3.5 Flash 2603?
Step 3.5 Flash leads overall capability (Intelligence Index 29.0 vs 29.0). Step 3.5 Flash 2603 is the cheaper model to run at $0.06/1M blended tokens — about 2.0× cheaper.
Which is better value?
Step 3.5 Flash 2603 offers more intelligence per dollar (2.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the Step 3.5 Flash 2603 if you want the lowest cost per token at scale.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.