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Mistral Large 4 vs GLM 5.3

Mistral Large 4

Mistral AI

69#133
vs
GLM 5.3

Zhipu AI

69#135
Signal-by-Signal Comparison
SignalMistral Large 4DeltaGLM 5.3
Capabilities
83
+17
67
Benchmarks
69
+1
69
Pricing
96
-3
98
Context window size
96
--
96
Recency
100
--
100
Output Capacity
87
-9
96
Overall Result
2 wins
of 6
2 wins
It's a tie - both models win 2 signals each

Score History

Score History (10 data points)
Mistral Large 4GLM 5.3
Mistral Large 4

69.1

current score

Leader

Mistral Large 4

right now

GLM 5.3

68.9

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Mistral Large 4

Mistral AI

Per request$0.003450
Daily$11.50
Monthly$345.00
Annual$4140.00

GLM 5.3

Zhipu AI

Best Value
Per request$0.000896
Daily$2.99
Monthly$89.58
Annual$1074.96

GLM 5.3 saves you $255.42/month

That's $3065.04/year compared to Mistral Large 4 at your current usage level of 100K calls/month.

74% cheaper
Choose GLM 5.3 for cost optimization

Mistral Large 4 pricing:
Input:$1.36/M tokens
Output:$4.18/M tokens
GLM 5.3 pricing:
Input:$0.09/M tokens
Output:$1.61/M tokens
Winner
Mistral Large 4

Mistral AI

69

Composite Score

GLM 5.3

Zhipu AI

69

Composite Score

Signal-by-Signal Comparison
MetricMistral Large 4GLM 5.3Winner
Overall Score
69
69
Mistral Large 4
Rank#133#135
Mistral Large 4
Quality Rank#133#135
Mistral Large 4
Adoption Rank#133#135
Mistral Large 4
Parameters------
Context Window1049K1049K--
Pricing$1.36/$4.18/M$0.09/$1.61/M--
Signal Scores
Capabilities
83
67
Mistral Large 4
Benchmarks
69
69
Mistral Large 4
Pricing
96
98
GLM 5.3
Context window size
96
96
Mistral Large 4
Recency
100
100
Mistral Large 4
Output Capacity
87
96
GLM 5.3
Benchmark Head-to-Head(9 benchmarks)
Mistral Large: 0GLM 5.3: 1
Mistral Large
GLM 5.3
Normalized 0-100%
MMLU
84.7%-
MMLU-Pro
69.4%86%
GPQA Diamond
52.5%-
MATH-500
76%-
HumanEval
92%-
IFEval
86.5%-
BBH
80%-
Arena Elo
1280-
BigCodeBench
30%-
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Mistral Large 4Competitive

Scores 69/100 (rank #133), placing it in the top 54% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 5.3Competitive

Scores 69/100 (rank #135), placing it in the top 54% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Mistral Large 4 when you need:

  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving

Choose GLM 5.3 when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Mistral Large 4
Input cost$1.36/M tokens
Output cost$4.18/M tokens
Cost per quality point$0.080
Est. monthly (1M tokens/day)$83.10
GLM 5.3Best Value
Input cost$0.09/M tokens
Output cost$1.61/M tokens
Cost per quality point$0.025
Est. monthly (1M tokens/day)$25.51

GLM 5.3 offers 69% better value per quality point. At 1M tokens/day, you'd spend $25.51/month with GLM 5.3 vs $83.10/month with Mistral Large 4 - a $57.59 monthly difference.

Latency & Speed
Mistral Large 4Faster
Speed score0/100
GLM 5.3
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Mistral Large 4

Customer support chatbot

Suitable for user-facing chat with competitive response times. GLM 5.3 also offers lower per-token costs for high-volume support

Mistral Large 4

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

Mistral Large 4

Batch data extraction

Lower output pricing ($1.61/M) reduces costs when processing thousands of records daily

GLM 5.3

Creative writing & content

Higher overall composite score (69/100) correlates with better nuance, coherence, and style in long-form content

Mistral Large 4

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Mistral Large 4
Which Should You Choose?
Our recommendation:
Mistral Large 4

Mistral Large 4 and GLM 5.3 are extremely close in overall performance (only 0.19999999999998863 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

Mistral Large 4
Recommended

by Mistral AI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Zhipu AI

  • Choose for Cost - 69% lower pricing; better value at scale
Capability Comparison
CapabilityMistral Large 4GLM 5.3
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Mistral Large 4

Mistral AI

$7.46
estimated monthly cost

GLM 5.3

Zhipu AI

Best Value
$2.10
estimated monthly cost

GLM 5.3 saves you $5.37/month

That's 72% cheaper than Mistral Large 4 at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterMistral Large 4GLM 5.3
Context Window1.0M1.0M
Max Output Tokens262,144943,718
Open SourceNoYes
CreatedOct 6, 2026Aug 18, 2026
Last updated: 1h ago

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Mistral Large 4 vs GLM 5.3 (2026) | LM Market Cap