Celeris-1 vs DeepSeek V4.1 Flash
Empirical evaluation across autonomous coding benchmarks (SWE-bench Verified, LiveCodeBench), token economics, and multi-agent topology in Swarm.
For autonomous agentic coding where multi-file patch pass rate is paramount, DeepSeek V4.1 Flash holds the verified advantage (-6.2% difference). Celeris-1 is 3x cheaper on input tokens ($0.1/M vs $0.3/M). In Swarm multi-agent clusters, Both models sit in Tier 3 (Tier 3: World-Record Throughput Reflex). Excellent peer redundancy or parallel Coder swarm execution.
Celeris-1
Finder SubagentDeepSeek V4.1 Flash
Coder SubagentStandardized Coding & Reasoning Benchmarks
Verified, contamination-free benchmark scores with direct mathematical deltas.
| Benchmark Metric | Celeris-1 | DeepSeek V4.1 Flash | Performance Delta |
|---|---|---|---|
| SWE-bench VerifiedReal-world GitHub issues resolved autonomously | 50% | 56.2% | DeepSeek V4.1 Flash (-6.2% difference) |
| LiveCodeBenchPost-training cutoff algorithmic challenges | 43% | 52% | DeepSeek V4.1 Flash (-9% difference) |
| LMSYS Coding EloCrowdsourced blind developer preference | — | 1360 | DeepSeek V4.1 Flash (Only measured on 1360) |
| AIME (Competition Math)Deep multi-step deductive reasoning | — | 74.5% | DeepSeek V4.1 Flash (Only measured on 74.5) |
Token Economics & Operational Cost Ratio
Pricing per 1M tokens and prompt caching advantages for long-horizon sessions.
Celeris-1 is 3x cheaper on input tokens ($0.1/M vs $0.3/M).
Output generation costs differ by 2.25x.
Prompt caching significantly reduces long-horizon AST parsing costs during multi-turn Swarm pairing sessions.
Swarm Multi-Agent Topology Synergy
How Swarm orchestrates Celeris-1 and DeepSeek V4.1 Flash in autonomous engineering clusters.
Celeris-1
Recommended: Finder Subagent
Executes instantaneous file discovery and grep tasks in parallel waves.
DeepSeek V4.1 Flash
Recommended: Coder Subagent
High throughput and low pricing make it optimal for Stage 2 implementation workers.
When to Choose Which Model
Practical developer recommendations based on real-world engineering workloads.
Choose Celeris-1 if:
- ✓World-record 1,492 TPS generation rate
- ✓Sub-100ms time-to-first-token on modern edge infrastructure
- ✓Ultra-low latency for interactive developer agent loops
- ✓Need Finder Subagent specialization inside Swarm.
Choose DeepSeek V4.1 Flash if:
- ✓Fast ~140 TPS execution
- ✓Strong JSON tool-calling syntax fidelity
- ✓Unbeatable economics for continuous integration agents
- ✓Need Coder Subagent specialization inside Swarm.
Frequently Asked Comparison Questions
Which model is better for autonomous software engineering: Celeris-1 or DeepSeek V4.1 Flash?
For autonomous agentic coding where multi-file patch pass rate is paramount, DeepSeek V4.1 Flash holds the verified advantage (-6.2% difference). Celeris-1 is 3x cheaper on input tokens ($0.1/M vs $0.3/M). In Swarm multi-agent clusters, Both models sit in Tier 3 (Tier 3: World-Record Throughput Reflex). Excellent peer redundancy or parallel Coder swarm execution. On SWE-bench Verified, Celeris-1 scores 50% vs DeepSeek V4.1 Flash at 56.2%.
How do Celeris-1 and DeepSeek V4.1 Flash compare on token pricing and operational economics?
Celeris-1 is 3x cheaper on input tokens ($0.1/M vs $0.3/M). On cached prompts, Celeris-1 costs $0.02/M vs DeepSeek V4.1 Flash at $0.05/M.
How does Swarm configure Celeris-1 and DeepSeek V4.1 Flash in multi-agent workflows?
Both models sit in Tier 3 (Tier 3: World-Record Throughput Reflex). 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.