Model comparison
Celeris-1 vs DeepSeek V4 Flash (High)
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Celeris-1 unranked (Not scored); DeepSeek V4 Flash (High) #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and DeepSeek V4 Flash (High) share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 37 to DeepSeek V4 Flash (High).
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- DeepSeek V4 Flash (High) only
- 37
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model; DeepSeek V4 Flash (High) is the better fit if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Celeris-1 and DeepSeek V4 Flash (High) finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Celeris-1 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 21.4x on output cost alone. DeepSeek V4 Flash (High) is the reasoning model in the pair, while Celeris-1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 8K for Celeris-1.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Celeris-1 | Δ | DeepSeek V4 Flash (High) |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 23.8 | DeepSeek V4 Flash (High)52.1 |
| Agentic | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Flash (High)55.3 |
| Coding | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Flash (High)68.5 |
| Math | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Flash (High)91.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 86.4%Winner: DeepSeek V4 Flash (High)Δ 10.5MMLU-Pro: Celeris-1 scored 75.9%; DeepSeek V4 Flash (High) scored 86.4%. DeepSeek V4 Flash (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | DeepSeek V4 Flash (High) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | DeepSeek V4 Flash (High)$0.14 input / $0.28 output | DeepSeek V4 Flash (High) has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | DeepSeek V4 Flash (High)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | DeepSeek V4 Flash (High)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | DeepSeek V4 Flash (High)1M | DeepSeek V4 Flash (High) lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 56.6% | Not comparable |
| BrowseCompSource | — | 53.5% | Not comparable |
| HLE w/ toolsSource | — | 40.3% | Not comparable |
| MCP AtlasSource | — | 67.4% | Not comparable |
| ToolathlonSource | — | 43.5% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| AA Agentic IndexSource | — | 28.2% | Not comparable |
| GDPval-AASource | — | 32.4% | Not comparable |
| GDPval-AASource | — | 1147 | Not comparable |
Coding7 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| CodeforcesSource | — | 2816.0 | Not comparable |
| SWE-bench VerifiedSource | — | 78.6% | Not comparable |
| SWE-bench ProSource | — | 52.3% | Not comparable |
| SWE MultilingualSource | — | 70.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 56.6% | Not comparable |
| AA-SciCodeSource | — | 42.0% | Not comparable |
| AA Coding IndexSource | — | 52.0% | Not comparable |
Reasoning4 benchmarks
KnowledgeCeleris-1 wins12 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 86.4% | DeepSeek V4 Flash (High) leads |
| SimpleQASource | — | 28.9% | Not comparable |
| Chinese-SimpleQASource | — | 73.2% | Not comparable |
| GPQASource | — | 87.4% | Not comparable |
| GPQA-DSource | — | 87.4% | Not comparable |
| HLESource | — | 29.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 37.5% | Not comparable |
| AA-GPQA DiamondSource | — | 86.7% | Not comparable |
| AA-HLESource | — | 27.8% | Not comparable |
| AA-Omniscience IndexSource | — | -22.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 35.5% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.7% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1238 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 73.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or DeepSeek V4 Flash (High)?
Celeris-1 and DeepSeek V4 Flash (High) are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Celeris-1 or DeepSeek V4 Flash (High)?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 52.1. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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