Model profile
StepFun
New in 2026

Step 3.5 Flash 2603

Step 3.5 Flash 2603 is a budget-priced text-first model from StepFun with fast runtime profile, partial context coverage, and the clearest fit around agent workflows / reasoning.

Best for: Agent workflows / ReasoningFast latencyN/A contextBudget pricing
Intelligence
38.5

Benchmark blend

Coding
34.6

Dev workflow signal

Context
N/A

N/A

Input Price
$0.00

Budget tier

Decision snapshot
59

Step 3.5 Flash 2603 currently reads as a budget text-first option with partially published context and a fast runtime profile.

Overall profile
Selective fit
Best for
Agent workflows / Reasoning
Latency tier
Fast
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
38.5
39

General reasoning and benchmark headroom.

Limited
Speed
180 tok/s
94

TTFT 0.81s

Above average
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

Step 3.5 Flash 2603 in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 35Math score N/A

The Step 3.5 Flash 2603 AI model by StepFun.

Identity

StepFun text-first profile

Positioning

Agent workflows / Reasoning with partially published context and fast runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Latency and throughput look responsive enough for interactive loops.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Context
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Intelligence
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Context
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
38.5
GPQA
82.6%
HLE
22.6%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
34.6
SciCode
38.5%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
66.5%
TAU2
87.4%
TerminalBench Hard
32.6%
LCR
54.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
$0.00

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.