Model comparison
DeepSeek V4 Flash (High) vs GLM-5.1
Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash (High) #92 (Estimated); GLM-5.1 #18 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash (High) and GLM-5.1 share 23 comparable benchmark results. 4 of 8 categories are comparable. 15 results are unique to DeepSeek V4 Flash (High); 13 to GLM-5.1.
Updated July 23, 2026- Shared results
- 23
- DeepSeek V4 Flash (High) only
- 15
- GLM-5.1 only
- 13
- Comparable categories
- 4 / 8
Pick GLM-5.1 if you want the stronger benchmark profile. DeepSeek V4 Flash (High) only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 7 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5.1 is clearly ahead on the BenchAlign aggregate, 67.74 to 53.95. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in agentic, where it averages 65.4 against 55.3. The single biggest benchmark swing on the page is HLE, 29.4% to 52.3%. DeepSeek V4 Flash (High) does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GLM-5.1 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 15.7x on output cost alone. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 203K for GLM-5.1.
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 | DeepSeek V4 Flash (High) | Δ | GLM-5.1 |
|---|---|---|---|
| Math | DeepSeek V4 Flash (High)91.9 | Margin← 29.9 | GLM-5.162.0 |
| Agentic | DeepSeek V4 Flash (High)55.3 | Margin→ 10.1 | GLM-5.165.4 |
| Coding | DeepSeek V4 Flash (High)68.5 | Margin← 7.2 | GLM-5.161.3 |
| Knowledge | DeepSeek V4 Flash (High)52.1 | Margin→ 0.2 | GLM-5.152.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 29.4%B 52.3%Winner: GLM-5.1Δ 22.9HLE: DeepSeek V4 Flash (High) scored 29.4%; GLM-5.1 scored 52.3%. GLM-5.1 wins this benchmark. - Source ↗
BrowseComp
AgenticA 53.5%B 68%Winner: GLM-5.1Δ 14.5BrowseComp: DeepSeek V4 Flash (High) scored 53.5%; GLM-5.1 scored 68%. GLM-5.1 wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 91.9%B 82.6%Winner: DeepSeek V4 Flash (High)Δ 9.3HMMT Feb 2026: DeepSeek V4 Flash (High) scored 91.9%; GLM-5.1 scored 82.6%. DeepSeek V4 Flash (High) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 56.6%B 63.5%Winner: GLM-5.1Δ 6.9Terminal-Bench 2.0: DeepSeek V4 Flash (High) scored 56.6%; GLM-5.1 scored 63.5%. GLM-5.1 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.3%B 58.4%Winner: GLM-5.1Δ 6.1SWE-bench Pro: DeepSeek V4 Flash (High) scored 52.3%; GLM-5.1 scored 58.4%. GLM-5.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash (High) | GLM-5.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash (High)$0.14 input / $0.28 output | GLM-5.1$1.4 input / $4.4 output | DeepSeek V4 Flash (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Flash (High)Not available | GLM-5.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash (High)Not available | GLM-5.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash (High)1M | GLM-5.1203K | DeepSeek V4 Flash (High) lists the larger context window. |
Benchmark Deep Dive
AgenticGLM-5.1 wins14 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.6% | 63.5% | GLM-5.1 leads |
| BrowseCompSource | 53.5% | 68% | GLM-5.1 leads |
| HLE w/ toolsSource | 40.3% | — | Not comparable |
| MCP AtlasSource | 67.4% | 71.8% | GLM-5.1 leads |
| ToolathlonSource | 43.5% | — | Not comparable |
| τ²-bench resultsSource | 95.6% | 97.7% | GLM-5.1 leads |
| AA Agentic IndexSource | 28.2% | 29.9% | GLM-5.1 leads |
| GDPval-AASource | 32.4% | 37.8% | GLM-5.1 leads |
| GDPval-AASource | 1147 | 1257 | GLM-5.1 leads |
| τ³-bench resultsSource | — | 70.6% | Not comparable |
| CyberGymSource | — | 68.7% | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| Gert LabsSource | — | 60.11% | Not comparable |
| ResearchClawBenchSource | — | 18.2% | Not comparable |
CodingDeepSeek V4 Flash (High) wins10 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| CodeforcesSource | 2816.0 | — | Not comparable |
| SWE-bench VerifiedSource | 78.6% | — | Not comparable |
| SWE-bench ProSource | 52.3% | 58.4% | GLM-5.1 leads |
| SWE MultilingualSource | 70.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 56.6% | — | Not comparable |
| AA-SciCodeSource | 42.0% | 43.8% | GLM-5.1 leads |
| AA Coding IndexSource | 52.0% | 55.8% | GLM-5.1 leads |
| NL2RepoSource | — | 42.7% | Not comparable |
| SWE-RebenchSource | — | 62.7% | Not comparable |
| Vibe Code BenchSource | — | 31.46% | Not comparable |
Reasoning4 benchmarks
KnowledgeGLM-5.1 wins12 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| MMLU-ProSource | 86.4% | — | Not comparable |
| SimpleQASource | 28.9% | — | Not comparable |
| Chinese-SimpleQASource | 73.2% | — | Not comparable |
| GPQASource | 87.4% | — | Not comparable |
| GPQA-DSource | 87.4% | 86.2% | DeepSeek V4 Flash (High) leads |
| HLESource | 29.4% | 52.3% | GLM-5.1 leads |
| Artificial Analysis Intelligence IndexSource | 37.5% | 40.2% | GLM-5.1 leads |
| AA-GPQA DiamondSource | 86.7% | 86.8% | GLM-5.1 leads |
| AA-HLESource | 27.8% | 28.0% | GLM-5.1 leads |
| AA-Omniscience IndexSource | -22.3% | 1.9% | GLM-5.1 leads |
| AA-Omniscience AccuracySource | 35.5% | 24.2% | DeepSeek V4 Flash (High) leads |
| AA-Omniscience Hallucination RateSource | 89.7% | 29.4% | GLM-5.1 leads |
MathDeepSeek V4 Flash (High) wins9 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 91.9% | 82.6% | DeepSeek V4 Flash (High) leads |
| IMOAnswerBenchSource | 85.1% | — | Not comparable |
| ApexSource | 19.1% | — | Not comparable |
| Apex ShortlistSource | 72.1% | — | Not comparable |
| AIME26Source | — | 95.3% | Not comparable |
| HMMT Nov 2025Source | — | 94.0% | Not comparable |
| MMAnswerBenchSource | — | 83.8% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 33.448% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 12.500% | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1238 | 1305 | GLM-5.1 leads |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | GLM-5.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.5% | 76.3% | GLM-5.1 leads |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Flash (High) or GLM-5.1?
GLM-5.1 is ahead on BenchLM's BenchAlign leaderboard, 67.74 to 53.95. The biggest single separator in this matchup is HLE, where the scores are 29.4% and 52.3%.
Which is better for knowledge tasks, DeepSeek V4 Flash (High) or GLM-5.1?
GLM-5.1 has the edge for knowledge tasks in this comparison, averaging 52.3 versus 52.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash (High) or GLM-5.1?
DeepSeek V4 Flash (High) has the edge for coding in this comparison, averaging 68.5 versus 61.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Flash (High) or GLM-5.1?
DeepSeek V4 Flash (High) has the edge for math in this comparison, averaging 91.9 versus 62. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash (High) or GLM-5.1?
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 55.3. Inside this category, GDPval-AA 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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