Model comparison
Celeris-1 vs DeepSeek V4 Pro
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 Pro #46 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and DeepSeek V4 Pro share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 22 to DeepSeek V4 Pro.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- DeepSeek V4 Pro only
- 22
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority; DeepSeek V4 Pro 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 Pro 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 $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro. That is roughly 6.9x on output cost alone. DeepSeek V4 Pro 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 Pro |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 34.6 | DeepSeek V4 Pro41.3 |
| Agentic | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Pro59.1 |
| Coding | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Pro65.3 |
| Math | Celeris-1Not measured | MarginNo overlap | DeepSeek V4 Pro31.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 82.9%Winner: DeepSeek V4 ProΔ 7MMLU-Pro: Celeris-1 scored 75.9%; DeepSeek V4 Pro scored 82.9%. DeepSeek V4 Pro 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 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | DeepSeek V4 Pro$0.435 input / $0.87 output | DeepSeek V4 Pro has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | DeepSeek V4 ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | DeepSeek V4 ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | DeepSeek V4 Pro1M | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeCeleris-1 wins6 benchmarks
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V4 Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1264 | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or DeepSeek V4 Pro?
Celeris-1 and DeepSeek V4 Pro 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 Pro?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 41.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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