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Model comparison

GLM-5.1 vs Step 3.7 Flash

Data verified

Head-to-head evidence from 22 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

67.76/100
Margin
17.0pts
← winning
50.76/100
1 category wins1 category wins

Verified leaderboard positions: GLM-5.1 #12; Step 3.7 Flash unranked

BenchAlign evidence: GLM-5.1 supported; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5.1 and Step 3.7 Flash share 22 comparable benchmark results. 2 of 8 categories are comparable. 15 results are unique to GLM-5.1; 8 to Step 3.7 Flash.

Updated July 16, 2026
Shared results
22
GLM-5.1 only
15
Step 3.7 Flash only
8
Comparable categories
2 / 8

Pick GLM-5.1 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if agentic is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 22 shared benchmark results across 6 evidence categories; 2 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 provisional aggregate, 67 to 57. 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 coding, where it averages 61.3 against 56.3. The single biggest benchmark swing on the page is BrowseComp, 68% to 75.8%. Step 3.7 Flash does hit back in agentic, 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 $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 3.8x on output cost alone. Step 3.7 Flash gives you the larger context window at 256K, 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 scores and score margins for GLM-5.1 and Step 3.7 Flash
CategoryGLM-5.1ΔStep 3.7 Flash
CodingGLM-5.161.3Margin← 5.0Step 3.7 Flash56.3
AgenticGLM-5.165.4Margin→ 1.0Step 3.7 Flash66.4
KnowledgeGLM-5.152.3MarginNo overlapStep 3.7 FlashNot measured
MathGLM-5.162.0MarginNo overlapStep 3.7 FlashNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · GLM-5.1B · Step 3.7 Flash

  1. BrowseComp

    Agentic
    Source ↗
    A 68%B 75.8%
    Winner: Step 3.7 FlashΔ 7.8
    BrowseComp: GLM-5.1 scored 68%; Step 3.7 Flash scored 75.8%. Step 3.7 Flash wins this benchmark.

  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 63.5%B 59.5%
    Winner: GLM-5.1Δ 4
    Terminal-Bench 2.0: GLM-5.1 scored 63.5%; Step 3.7 Flash scored 59.5%. GLM-5.1 wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 58.4%B 56.3%
    Winner: GLM-5.1Δ 2.1
    SWE-bench Pro: GLM-5.1 scored 58.4%; Step 3.7 Flash scored 56.3%. GLM-5.1 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGLM-5.1Step 3.7 FlashComparison
Input / output priceUSD per 1M tokensGLM-5.1$1.4 input / $4.4 outputStep 3.7 Flash$0.2 input / $1.15 outputStep 3.7 Flash has the lower combined listed price.
Generation speedtokens per secondGLM-5.1Not availableStep 3.7 FlashNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-5.1Not availableStep 3.7 FlashNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-5.1203KStep 3.7 Flash256KStep 3.7 Flash lists the larger context window.

Benchmark Deep Dive

AgenticStep 3.7 Flash wins
BenchmarkGLM-5.1Step 3.7 FlashResult
Terminal-Bench 2.0Source 63.5%59.5%GLM-5.1 leads
BrowseCompSource 68%75.8%Step 3.7 Flash leads
τ³-bench resultsSource 70.6%—Not comparable
MCP AtlasSource 71.8%—Not comparable
CyberGymSource 68.7%—Not comparable
Claw-EvalSource 62.3%67.1%Step 3.7 Flash leads
AA Agentic IndexSource 29.9%21.5%GLM-5.1 leads
τ²-bench resultsSource 97.7%98.5%Step 3.7 Flash leads
GDPval-AASource 37.8%25.9%GLM-5.1 leads
Gert LabsSource 60.11%51.57%GLM-5.1 leads
GDPval-AASource 12571017GLM-5.1 leads
ResearchClawBenchSource 18.2%—Not comparable
DeepSearchQASource —92.8%Not comparable
ToolathlonSource —49.5%Not comparable
HLE w/ toolsSource —47.2%Not comparable
APEX-Agents-AASource —14.8%Not comparable
CodingGLM-5.1 wins
BenchmarkGLM-5.1Step 3.7 FlashResult
SWE-bench ProSource 58.4%56.3%GLM-5.1 leads
NL2RepoSource 42.7%—Not comparable
SWE-RebenchSource 62.7%—Not comparable
Vibe Code BenchSource 31.46%—Not comparable
AA Coding IndexSource 55.8%39.6%GLM-5.1 leads
Terminal-Bench HardSource 43.2%35.6%GLM-5.1 leads
AA-SciCodeSource 43.8%40.0%GLM-5.1 leads
Terminal-Bench 2.0Source —59.5%Not comparable
Reasoning
BenchmarkGLM-5.1Step 3.7 FlashResult
AA-LCRSource 62.3%63.7%Step 3.7 Flash leads
CritPtSource 4.6%2.3%GLM-5.1 leads
Knowledge
BenchmarkGLM-5.1Step 3.7 FlashResult
GPQA-DSource 86.2%—Not comparable
HLESource 52.3%—Not comparable
Artificial Analysis Intelligence IndexSource 40.2%30.3%GLM-5.1 leads
AA-GPQA DiamondSource 86.8%80.9%GLM-5.1 leads
AA-HLESource 28.0%19.9%GLM-5.1 leads
AA-Omniscience IndexSource 1.9%-37.5%GLM-5.1 leads
AA-Omniscience AccuracySource 24.2%25.4%Step 3.7 Flash leads
AA-Omniscience Hallucination RateSource 29.4%84.4%GLM-5.1 leads
Math
BenchmarkGLM-5.1Step 3.7 FlashResult
AIME26Source 95.3%—Not comparable
HMMT Nov 2025Source 94.0%—Not comparable
HMMT Feb 2026Source 82.6%—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
Multimodal
BenchmarkGLM-5.1Step 3.7 FlashResult
Design Arena WebsiteSource 13121218GLM-5.1 leads
SimpleVQASource —79.2%Not comparable
V*Source —95.3%Not comparable
AA-MMMU-ProSource —75.3%Not comparable
Inst. Following
BenchmarkGLM-5.1Step 3.7 FlashResult
AA-IFBenchSource 76.3%67.3%GLM-5.1 leads
Frequently Asked Questions (3)

Which is better, GLM-5.1 or Step 3.7 Flash?

GLM-5.1 is ahead on BenchLM's provisional leaderboard, 67 to 57. The biggest single separator in this matchup is BrowseComp, where the scores are 68% and 75.8%.

Which is better for coding, GLM-5.1 or Step 3.7 Flash?

GLM-5.1 has the edge for coding in this comparison, averaging 61.3 versus 56.3. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GLM-5.1 or Step 3.7 Flash?

Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 66.4 versus 65.4. 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.

GLM-5.1
API / mo$4,350
Self-host / mo$18,221
Break-even264M/day
Step 3.7 Flash
API / mo$1,012
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

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