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Model comparison

GLM-5.1 vs Mistral Medium 3.5 128B

Data verified

Head-to-head evidence from 17 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.84/100
No comparison
0 category wins1 category wins

Public leaderboard positions: GLM-5.1 #22 (Supported); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5.1 and Mistral Medium 3.5 128B share 17 comparable benchmark results. 1 of 8 categories are comparable. 19 results are unique to GLM-5.1; 8 to Mistral Medium 3.5 128B.

Updated July 27, 2026
Shared results
17
GLM-5.1 only
19
Mistral Medium 3.5 128B only
8
Comparable categories
1 / 8

Treat this as a split decision. GLM-5.1 makes more sense if you want the cheaper token bill; Mistral Medium 3.5 128B is the better fit if coding is the priority or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 5 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-5.1 and Mistral Medium 3.5 128B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Mistral Medium 3.5 128B is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.1. Mistral Medium 3.5 128B 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 Mistral Medium 3.5 128B
CategoryGLM-5.1ΔMistral Medium 3.5 128B
CodingGLM-5.161.3Margin 16.3Mistral Medium 3.5 128B77.6
AgenticGLM-5.165.4MarginNo overlapMistral Medium 3.5 128BNot measured
KnowledgeGLM-5.152.3MarginNo overlapMistral Medium 3.5 128BNot measured
MathGLM-5.162.0MarginNo overlapMistral Medium 3.5 128BNot measured

Operational comparison

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

MetricGLM-5.1Mistral Medium 3.5 128BComparison
Input / output priceUSD per 1M tokensGLM-5.1$1.4 input / $4.4 outputMistral Medium 3.5 128B$1.5 input / $7.5 outputGLM-5.1 has the lower combined listed price.
Generation speedtokens per secondGLM-5.1Not availableMistral Medium 3.5 128BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-5.1Not availableMistral Medium 3.5 128BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-5.1203KMistral Medium 3.5 128B256KMistral Medium 3.5 128B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
Terminal-Bench 2.0Source 63.5%Not comparable
BrowseCompSource 68%Not comparable
τ³-bench resultsSource 70.6%91.4%Mistral Medium 3.5 128B leads
MCP AtlasSource 71.8%Not comparable
CyberGymSource 68.7%Not comparable
Claw-EvalSource 62.3%Not comparable
AA Agentic IndexSource 29.9%19.0%GLM-5.1 leads
τ²-bench resultsSource 97.7%94.2%GLM-5.1 leads
GDPval-AASource 37.8%21.6%GLM-5.1 leads
Gert LabsSource 60.11%39.10%GLM-5.1 leads
GDPval-AASource 1256933GLM-5.1 leads
ResearchClawBenchSource 18.2%Not comparable
AA EnterpriseOps-GymSource 33.7%Not comparable
AA Harvey LABSource 69.1%Not comparable
terminalBenchHardSource 33.3%Not comparable
AA BriefcaseSource 516Not comparable
AA Tau3 BankingSource 14.4%Not comparable
CodingMistral Medium 3.5 128B wins
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
SWE-bench ProSource 58.4%Not comparable
NL2RepoSource 42.7%Not comparable
SWE-RebenchSource 62.7%Not comparable
Vibe Code BenchSource 31.46%Not comparable
AA Coding IndexSource 55.8%46.9%GLM-5.1 leads
AA-SciCodeSource 43.8%39.6%GLM-5.1 leads
SWE-bench VerifiedSource 77.6%Not comparable
Reasoning
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
AA-LCRSource 62.3%61.0%GLM-5.1 leads
CritPtSource 4.6%0.0%GLM-5.1 leads
Knowledge
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
GPQA-DSource 86.2%Not comparable
HLESource 52.3%Not comparable
Artificial Analysis Intelligence IndexSource 40.2%29.9%GLM-5.1 leads
AA-GPQA DiamondSource 86.8%74.8%GLM-5.1 leads
AA-HLESource 28.0%12.8%GLM-5.1 leads
AA-Omniscience IndexSource 1.9%-36.3%GLM-5.1 leads
AA-Omniscience AccuracySource 24.2%25.1%Mistral Medium 3.5 128B leads
AA-Omniscience Hallucination RateSource 29.4%82.0%GLM-5.1 leads
AA Openness IndexSource 33.3%Not comparable
Math
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
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-5.1Mistral Medium 3.5 128BResult
Design Arena WebsiteSource 1299Not comparable
AA-MMMU-ProSource 64.9%Not comparable
Inst. Following
BenchmarkGLM-5.1Mistral Medium 3.5 128BResult
AA-IFBenchSource 76.3%68.8%GLM-5.1 leads
Frequently Asked Questions (2)

Which is better, GLM-5.1 or Mistral Medium 3.5 128B?

GLM-5.1 and Mistral Medium 3.5 128B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for coding, GLM-5.1 or Mistral Medium 3.5 128B?

Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 61.3. Inside this category, AA Coding Index 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
Mistral Medium 3.5 128B
API / mo$6,750
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 27, 2026

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