Model comparison
GLM-4.6 vs Llama 4 Scout
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.6 #85 (Supported); Llama 4 Scout #174 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.6 and Llama 4 Scout share 12 comparable benchmark results. 0 of 8 categories are comparable. 2 results are unique to GLM-4.6; 6 to Llama 4 Scout.
Updated July 23, 2026- Shared results
- 12
- GLM-4.6 only
- 2
- Llama 4 Scout only
- 6
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.6 and Llama 4 Scout is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 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 200K for GLM-4.6.
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 | GLM-4.6 | Δ | Llama 4 Scout |
|---|---|---|---|
| Math | GLM-4.63.4 | MarginNo overlap | Llama 4 ScoutNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 3.819%B 0.000%Winner: GLM-4.6Δ 3.8FrontierMath v2 (Tiers 1-3): GLM-4.6 scored 3.819%; Llama 4 Scout scored 0.000%. GLM-4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.6 | Llama 4 Scout | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.6Not available | Llama 4 Scout$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.6Not available | Llama 4 Scout128 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.6Not available | Llama 4 Scout0.70 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.6200K | Llama 4 Scout10M | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GLM-4.6 | Llama 4 Scout | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.0% | 10.0% | GLM-4.6 leads |
| AA-GPQA DiamondSource | 63.2% | 58.7% | GLM-4.6 leads |
| AA-HLESource | 5.2% | 4.3% | GLM-4.6 leads |
| AA-Omniscience IndexSource | -31.6% | -52.4% | GLM-4.6 leads |
| AA-Omniscience AccuracySource | 20.8% | 14.6% | GLM-4.6 leads |
| AA-Omniscience Hallucination RateSource | 66.1% | 78.3% | GLM-4.6 leads |
Math2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.6 | Llama 4 Scout | Result |
|---|---|---|---|
| AA-IFBenchSource | 36.7% | 39.5% | Llama 4 Scout leads |
Frequently Asked Questions (3)
Can I compare GLM-4.6 and Llama 4 Scout 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 GLM-4.6 and Llama 4 Scout today?
Llama 4 Scout: $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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