Model comparison
Celeris-1 vs DeepSeek V3.2
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Celeris-1 unranked (Not scored); DeepSeek V3.2 #82 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and DeepSeek V3.2 share 0 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to Celeris-1; 19 to DeepSeek V3.2.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- DeepSeek V3.2 only
- 19
- Comparable categories
- 0 / 8
Benchmark data for Celeris-1 and DeepSeek V3.2 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Celeris-1 is priced at $2.00 input / $6.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. DeepSeek V3.2 has the larger context window at 128K, compared with 8K for Celeris-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | DeepSeek V3.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | DeepSeek V3.2$0.28 input / $0.42 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | DeepSeek V3.235 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | DeepSeek V3.23.75 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | DeepSeek V3.2128K | DeepSeek V3.2 lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3.2 | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 24.7% | Not comparable |
| AA-GPQA DiamondSource | — | 75.1% | Not comparable |
| AA-HLESource | — | 10.5% | Not comparable |
| AA-Omniscience IndexSource | — | -46.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 93.5% | Not comparable |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3.2 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1204 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | DeepSeek V3.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 49.0% | Not comparable |
Frequently Asked Questions (3)
Can I compare Celeris-1 and DeepSeek V3.2 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Celeris-1 and DeepSeek V3.2 today?
Celeris-1: $2.00 input / $6.00 output per 1M tokens DeepSeek V3.2: $0.28 input / $0.42 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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