Model comparison
Llama 4 Scout vs MiMo-V2-Flash
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Scout #174 (Supported); MiMo-V2-Flash #91 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Scout and MiMo-V2-Flash share 15 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to Llama 4 Scout; 4 to MiMo-V2-Flash.
Updated July 22, 2026- Shared results
- 15
- Llama 4 Scout only
- 3
- MiMo-V2-Flash only
- 4
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Scout and MiMo-V2-Flash is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 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.
Llama 4 Scout has the larger context window at 10M, compared with 256K for MiMo-V2-Flash.
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 | Llama 4 Scout | Δ | MiMo-V2-Flash |
|---|---|---|---|
| Coding | Llama 4 ScoutNot measured | MarginNo overlap | MiMo-V2-Flash73.4 |
| Knowledge | Llama 4 ScoutNot measured | MarginNo overlap | MiMo-V2-Flash84.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Scout | MiMo-V2-Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Scout$0 input / $0 output | MiMo-V2-Flash$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Llama 4 Scout128 tok/s | MiMo-V2-Flash129 tok/s | MiMo-V2-Flash has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Scout0.70 s | MiMo-V2-Flash2.14 s | Llama 4 Scout reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Scout10M | MiMo-V2-Flash256K | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Llama 4 Scout | MiMo-V2-Flash | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | 24.7% | MiMo-V2-Flash leads |
| AA-GPQA DiamondSource | 58.7% | 65.6% | MiMo-V2-Flash leads |
| AA-HLESource | 4.3% | 8.0% | MiMo-V2-Flash leads |
| AA-Omniscience IndexSource | -52.4% | -48.5% | MiMo-V2-Flash leads |
| AA-Omniscience AccuracySource | 14.6% | 15.2% | MiMo-V2-Flash leads |
| AA-Omniscience Hallucination RateSource | 78.3% | 75.1% | MiMo-V2-Flash leads |
| GPQASource | — | 83.7% | Not comparable |
| MMLU-ProSource | — | 84.9% | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Llama 4 Scout | MiMo-V2-Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 39.5% | 39.9% | MiMo-V2-Flash leads |
Frequently Asked Questions (3)
Can I compare Llama 4 Scout and MiMo-V2-Flash 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 Llama 4 Scout and MiMo-V2-Flash today?
Llama 4 Scout: $0.00 input / $0.00 output per 1M tokens MiMo-V2-Flash: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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