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Codestral 2508 vs GLM 5.2

Codestral 2508

Mistral AI

40#267
vs
GLM 5.2

Zhipu AI

79#68
Signal-by-Signal Comparison
SignalCodestral 2508DeltaGLM 5.2
Capabilities
50
-17
67
Pricing
99
+1
98
Context window size
86
-10
96
Recency
67
-33
100
Output Capacity
20
-65
85
Benchmarks
0
-80
81
Overall Result
1 wins
of 6
5 wins
GLM 5.2 wins 5 of 6 signals

Score History

Score History (24 data points)
Codestral 2508GLM 5.2
Codestral 2508

40

current score

Leader

GLM 5.2

right now

GLM 5.2

78.5

current score

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

Codestral 2508

Mistral AI

Best Value
Per request$0.000750
Daily$2.50
Monthly$75.00
Annual$900.00

GLM 5.2

Zhipu AI

Per request$0.001890
Daily$6.30
Monthly$189.00
Annual$2268.00

Codestral 2508 saves you $114.00/month

That's $1368.00/year compared to GLM 5.2 at your current usage level of 100K calls/month.

60% cheaper
Choose Codestral 2508 for cost optimization

Codestral 2508 pricing:
Input:$0.30/M tokens
Output:$0.90/M tokens
GLM 5.2 pricing:
Input:$0.73/M tokens
Output:$2.31/M tokens
Codestral 2508

Mistral AI

40

Composite Score

Winner
GLM 5.2

Zhipu AI

79

Composite Score

Signal-by-Signal Comparison
MetricCodestral 2508GLM 5.2Winner
Overall Score
40
79
GLM 5.2
Rank#267#68
GLM 5.2
Quality Rank#267#68
GLM 5.2
Adoption Rank#267#68
GLM 5.2
Parameters------
Context Window256K1049K
GLM 5.2
Pricing$0.30/$0.90/M$0.73/$2.31/M--
Signal Scores
Capabilities
50
67
GLM 5.2
Pricing
99
98
Codestral 2508
Context window size
86
96
GLM 5.2
Recency
67
100
GLM 5.2
Output Capacity
20
85
GLM 5.2
Benchmarks--
81
GLM 5.2
Benchmark Head-to-Head(2 benchmarks)
Codestral 2508: 0GLM 5.2: 0
Codestral 2508
GLM 5.2
Normalized 0-100%
MMLU-Pro
-86%
Arena Elo
-1457
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.

Codestral 2508Entry Level

Scores 40/100 (rank #267), placing it in the top 8% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 5.2Strong Performer

Scores 79/100 (rank #68), placing it in the top 77% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

GLM 5.2 has a 39-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose Codestral 2508 when you need:

  • High-volume production workloads where API costs must be minimized

Choose GLM 5.2 when you need:

  • Processing long documents or large codebases (1049K token context)
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Codestral 2508Best Value
Input cost$0.30/M tokens
Output cost$0.90/M tokens
Cost per quality point$0.030
Est. monthly (1M tokens/day)$18.00
GLM 5.2
Input cost$0.73/M tokens
Output cost$2.31/M tokens
Cost per quality point$0.039
Est. monthly (1M tokens/day)$45.67

Codestral 2508 offers 61% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with Codestral 2508 vs $45.67/month with GLM 5.2 - a $27.67 monthly difference.

Latency & Speed
Codestral 2508Faster
Speed score0/100
GLM 5.2
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

Codestral 2508

Customer support chatbot

Suitable for user-facing chat with competitive response times. Codestral 2508 also offers lower per-token costs for high-volume support

Codestral 2508

Long document analysis

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

GLM 5.2

Batch data extraction

Lower output pricing ($0.90/M) reduces costs when processing thousands of records daily

Codestral 2508

Creative writing & content

Higher overall composite score (79/100) correlates with better nuance, coherence, and style in long-form content

GLM 5.2
Which Should You Choose?
Our recommendation:
GLM 5.2

GLM 5.2 clearly outperforms Codestral 2508 with a significant 38.5-point lead. For most general use cases, GLM 5.2 is the stronger choice. However, Codestral 2508 may still excel in niche scenarios.

by Mistral AI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 61% lower pricing; better value at scale
  • 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
GLM 5.2
Recommended

by Zhipu AI

Consider for specialized use cases.

Capability Comparison
CapabilityCodestral 2508GLM 5.2
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Codestral 2508

Mistral AI

Best Value
$1.62
estimated monthly cost

GLM 5.2

Zhipu AI

$4.09
estimated monthly cost

Codestral 2508 saves you $2.47/month

That's 60% cheaper than GLM 5.2 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
ParameterCodestral 2508GLM 5.2
Context Window256K1.0M
Max Output Tokens--131,072
Open SourceNoYes
CreatedAug 1, 2025Jun 16, 2026
Last updated: 57m ago

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Codestral 2508 vs GLM 5.2 (2026) | LM Market Cap