Model comparison
Celeris-1 vs DeepSeek V3
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 V3 #147 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and DeepSeek V3 share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 21 to DeepSeek V3.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- DeepSeek V3 only
- 21
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority; DeepSeek V3 is the better fit if you want the cheaper token bill or you need the larger 128K 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 V3 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 $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 5.5x on output cost alone. DeepSeek V3 gives you the larger context window at 128K, 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 V3 |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 3.2 | DeepSeek V372.7 |
| Coding | Celeris-1Not measured | MarginNo overlap | DeepSeek V338.9 |
| Math | Celeris-1Not measured | MarginNo overlap | DeepSeek V31.7 |
| Inst. Following | Celeris-1Not measured | MarginNo overlap | DeepSeek V386.1 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | DeepSeek V3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | DeepSeek V3$0.27 input / $1.1 output | DeepSeek V3 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | DeepSeek V3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | DeepSeek V3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | DeepSeek V3128K | DeepSeek V3 lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeCeleris-1 wins8 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3 | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 75.9% | Tie |
| GPQASource | — | 59.1% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 14.2% | Not comparable |
| AA-GPQA DiamondSource | — | 55.7% | Not comparable |
| AA-HLESource | — | 3.6% | Not comparable |
| AA-Omniscience IndexSource | — | -41.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 25.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.4% | Not comparable |
Math1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | — | 1.724% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1150 | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or DeepSeek V3?
Celeris-1 and DeepSeek V3 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 V3?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 72.7. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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