Model comparison
Celeris-1 vs MiMo-V2-Flash
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); MiMo-V2-Flash #91 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and MiMo-V2-Flash share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 18 to MiMo-V2-Flash.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- MiMo-V2-Flash only
- 18
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; MiMo-V2-Flash is the better fit if knowledge is the priority or you want the cheaper token bill.
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 MiMo-V2-Flash 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 $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. MiMo-V2-Flash 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. MiMo-V2-Flash gives you the larger context window at 256K, 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 | MiMo-V2-Flash |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin→ 8.8 | MiMo-V2-Flash84.7 |
| Coding | Celeris-1Not measured | MarginNo overlap | MiMo-V2-Flash73.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 84.9%Winner: MiMo-V2-FlashΔ 9MMLU-Pro: Celeris-1 scored 75.9%; MiMo-V2-Flash scored 84.9%. MiMo-V2-Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | MiMo-V2-Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | MiMo-V2-Flash$0 input / $0 output | MiMo-V2-Flash has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | MiMo-V2-Flash129 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | MiMo-V2-Flash2.14 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | MiMo-V2-Flash256K | MiMo-V2-Flash lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
KnowledgeMiMo-V2-Flash wins8 benchmarks
| Benchmark | Celeris-1 | MiMo-V2-Flash | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 84.9% | MiMo-V2-Flash leads |
| GPQASource | — | 83.7% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 24.7% | Not comparable |
| AA-GPQA DiamondSource | — | 65.6% | Not comparable |
| AA-HLESource | — | 8.0% | Not comparable |
| AA-Omniscience IndexSource | — | -48.5% | Not comparable |
| AA-Omniscience AccuracySource | — | 15.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 75.1% | Not comparable |
Math1 benchmarks
| Benchmark | Celeris-1 | MiMo-V2-Flash | Result |
|---|---|---|---|
| AIME 2025Source | — | 94.1% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | MiMo-V2-Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 39.9% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or MiMo-V2-Flash?
Celeris-1 and MiMo-V2-Flash 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 MiMo-V2-Flash?
MiMo-V2-Flash has the edge for knowledge tasks in this comparison, averaging 84.7 versus 75.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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