HEAD-TO-HEAD BENCHMARK COMPARISONTier 1 vs Tier 1

Kimi K3 vs Step 5 Preview

Empirical evaluation across autonomous coding benchmarks (SWE-bench Verified, LiveCodeBench), token economics, and multi-agent topology in Swarm.

TECHNICAL VERDICT

For autonomous agentic coding where multi-file patch pass rate is paramount, Kimi K3 holds the verified advantage (+0.7% advantage). Both models share identical input pricing at $1/M. In Swarm multi-agent clusters, Both models sit in Tier 1 (Tier 1: Long-Context Architect). Excellent peer redundancy or parallel Coder swarm execution.

Kimi K3

Primary / Planner
SWE-bench Verified:70.2%
LiveCodeBench:62%
Pricing (In / Out):$1 / $5
VS

Step 5 Preview

Coder Subagent
SWE-bench Verified:69.5%
LiveCodeBench:61.8%
Pricing (In / Out):$1 / $5

Standardized Coding & Reasoning Benchmarks

Verified, contamination-free benchmark scores with direct mathematical deltas.

Benchmark MetricKimi K3Step 5 PreviewPerformance Delta
SWE-bench VerifiedReal-world GitHub issues resolved autonomously70.2%69.5%Kimi K3 (+0.7% advantage)
LiveCodeBenchPost-training cutoff algorithmic challenges62%61.8%Kimi K3 (+0.2% advantage)
LMSYS Coding EloCrowdsourced blind developer preference13901388Kimi K3 (+2Elo advantage)
AIME (Competition Math)Deep multi-step deductive reasoning——Not published for both models

Token Economics & Operational Cost Ratio

Pricing per 1M tokens and prompt caching advantages for long-horizon sessions.

Prompt Input Tokens
Kimi K3$1 / 1M
Step 5 Preview$1 / 1M

Both models share identical input pricing at $1/M.

Completion Output Tokens
Kimi K3$5 / 1M
Step 5 Preview$5 / 1M

Both models share identical completion pricing.

Context Caching Advantage
Kimi K3$$0.15 / 1M
Step 5 Preview$$0.15 / 1M

Prompt caching significantly reduces long-horizon AST parsing costs during multi-turn Swarm pairing sessions.

Swarm Multi-Agent Topology Synergy

How Swarm orchestrates Kimi K3 and Step 5 Preview in autonomous engineering clusters.

⚡

Optimal Cluster Configuration

Both models sit in Tier 1 (Tier 1: Long-Context Architect). Excellent peer redundancy or parallel Coder swarm execution.

Tier 1

Kimi K3

Ingests large dependency graphs to construct accurate Task Program DAG stages.

Worktree Isolation: Plans holistic multi-subsystem changes across distinct worktrees.
Tier 1

Step 5 Preview

Reliable coding subagent that self-corrects test regressions before committing.

Worktree Isolation: Performs iterative test fixes cleanly in worktrees without human intervention.

When to Choose Which Model

Practical developer recommendations based on real-world engineering workloads.

Choose Kimi K3 if:

  • ✓Intelligence Index 44 with outstanding 47 Finance & Accounting score
  • ✓Large 2M token context window for full-repo architectural planning
  • ✓Cost-efficient $1.20 cost per task with high code synthesis precision
  • ✓Need Primary / Planner specialization inside Swarm.

Choose Step 5 Preview if:

  • ✓Intelligence Index 44 with balanced $1.10 cost per task
  • ✓Clean self-correcting feedback loops during code compilation
  • ✓Strong multilingual reasoning and docstring generation
  • ✓Need Coder Subagent specialization inside Swarm.

Frequently Asked Comparison Questions

Which model is better for autonomous software engineering: Kimi K3 or Step 5 Preview?

For autonomous agentic coding where multi-file patch pass rate is paramount, Kimi K3 holds the verified advantage (+0.7% advantage). Both models share identical input pricing at $1/M. In Swarm multi-agent clusters, Both models sit in Tier 1 (Tier 1: Long-Context Architect). Excellent peer redundancy or parallel Coder swarm execution. On SWE-bench Verified, Kimi K3 scores 70.2% vs Step 5 Preview at 69.5%.

How do Kimi K3 and Step 5 Preview compare on token pricing and operational economics?

Both models share identical input pricing at $1/M. On cached prompts, Kimi K3 costs $0.15/M vs Step 5 Preview at $0.15/M.

How does Swarm configure Kimi K3 and Step 5 Preview in multi-agent workflows?

Both models sit in Tier 1 (Tier 1: Long-Context Architect). Excellent peer redundancy or parallel Coder swarm execution. Swarm isolates code modifications in independent Git worktrees, allowing both models to operate in parallel without colliding working directories or git branch conflicts.

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