Model comparison
DeepSeek V3 vs GLM-4.6
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: DeepSeek V3 #147 (Supported); GLM-4.6 #85 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3 and GLM-4.6 share 12 comparable benchmark results. 1 of 8 categories are comparable. 10 results are unique to DeepSeek V3; 2 to GLM-4.6.
Updated July 23, 2026- Shared results
- 12
- DeepSeek V3 only
- 10
- GLM-4.6 only
- 2
- Comparable categories
- 1 / 8
Pick GLM-4.6 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-4.6 is clearly ahead on the BenchAlign aggregate, 55.12 to 44.97. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.6's sharpest advantage is in mathematics, where it averages 3.4 against 1.7. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 1.724% to 3.819%.
GLM-4.6 is the reasoning model in the pair, while DeepSeek V3 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. GLM-4.6 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.
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 | DeepSeek V3 | Δ | GLM-4.6 |
|---|---|---|---|
| Math | DeepSeek V31.7 | Margin→ 1.7 | GLM-4.63.4 |
| Coding | DeepSeek V338.9 | MarginNo overlap | GLM-4.6Not measured |
| Knowledge | DeepSeek V372.7 | MarginNo overlap | GLM-4.6Not measured |
| Inst. Following | DeepSeek V386.1 | MarginNo overlap | GLM-4.6Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 1.724%B 3.819%Winner: GLM-4.6Δ 2.1FrontierMath v2 (Tiers 1-3): DeepSeek V3 scored 1.724%; GLM-4.6 scored 3.819%. GLM-4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3 | GLM-4.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3$0.27 input / $1.1 output | GLM-4.6Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3Not available | GLM-4.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3Not available | GLM-4.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3128K | GLM-4.6200K | GLM-4.6 lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding5 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | DeepSeek V3 | GLM-4.6 | Result |
|---|---|---|---|
| GPQASource | 59.1% | — | Not comparable |
| MMLU-ProSource | 75.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.2% | 23.0% | GLM-4.6 leads |
| AA-GPQA DiamondSource | 55.7% | 63.2% | GLM-4.6 leads |
| AA-HLESource | 3.6% | 5.2% | GLM-4.6 leads |
| AA-Omniscience IndexSource | -41.3% | -31.6% | GLM-4.6 leads |
| AA-Omniscience AccuracySource | 25.4% | 20.8% | DeepSeek V3 leads |
| AA-Omniscience Hallucination RateSource | 89.4% | 66.1% | GLM-4.6 leads |
MathGLM-4.6 wins2 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3 | GLM-4.6 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1150 | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V3 or GLM-4.6?
GLM-4.6 is ahead on BenchLM's BenchAlign leaderboard, 55.12 to 44.97. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 1.724% and 3.819%.
Which is better for math, DeepSeek V3 or GLM-4.6?
GLM-4.6 has the edge for math in this comparison, averaging 3.4 versus 1.7. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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