# GLM-5 vs Kimi K2.5 vs Codex 5.3 vs Claude Opus 4.6 vs Sonnet 4.6 vs MiniMax M2.5

## Agentic Coding Model Comparison Report

**Generated:** 2026-03-01  
**Models Compared:** 6  

## Executive Summary

| Model | SWE-bench Est. | Input $/1M | Output $/1M | Context | Opus Replacement Score |
|-------|----------------|------------|-------------|---------|------------------------|
| GLM-5 | Not officially benchmarked on SWE-bench Verified as of March 2025 [uncertain] | $0.50 (API pricing via Zhipu AI platform) | $2.00 (API pricing via Zhipu AI platform) | 128K tokens | 5/10 |
| Kimi K2.5 | ~48-52% on SWE-bench Verified (reported by community) [uncertain] | $2.00 (standard), $1.00 (batch) | $8.00 (standard), $4.00 (batch) | 256K tokens (up to 2M in beta for some use cases) | 8/10 |
| Codex 5.3 | ~55-60% on SWE-bench Verified (estimated from early reports) [uncertain] | $3.00 (Codex specific API) | $12.00 (Codex specific API) | 128K tokens | 9/10 |
| Claude Opus 4.6 | ~60-65% on SWE-bench Verified (state-of-the-art as of early 2025) [uncertain] | $5.00 | $15.00 | 200K tokens | 10/10 |
| Claude Sonnet 4.6 | ~50-55% on SWE-bench Verified (estimated from comparisons) [uncertain] | $3.00 | $15.00 | 200K tokens | 9/10 |
| MiniMax M2.5 | ~40-45% on SWE-bench Verified (estimated from early testing) [uncertain] | $0.50 | $2.00 | 100K tokens | 6/10 |

## Table of Contents

1. [GLM-5](#glm-5) - Replacement Score: 5/10 | Input: $0.50 (API pricing via Zhipu AI platform)
2. [Kimi K2.5](#kimi-k2.5) - Replacement Score: 8/10 | Input: $2.00 (standard), $1.00 (batch)
3. [Codex 5.3](#codex-5.3) - Replacement Score: 9/10 | Input: $3.00 (Codex specific API)
4. [Claude Opus 4.6](#claude-opus-4.6) - Replacement Score: 10/10 | Input: $5.00
5. [Claude Sonnet 4.6](#claude-sonnet-4.6) - Replacement Score: 9/10 | Input: $3.00
6. [MiniMax M2.5](#minimax-m2.5) - Replacement Score: 6/10 | Input: $0.50

## GLM-5

### Performance Benchmarks

**Swe Bench Verified Score:** Not officially benchmarked on SWE-bench Verified as of March 2025 [uncertain] [uncertain]

**Swe Bench Full Score:** N/A [uncertain] [uncertain]

**Swe Bench Lite Score:** N/A [uncertain] [uncertain]

**Other Coding Benchmarks:** Strong performance on Chinese coding benchmarks; competitive with GPT-4 on select tasks [uncertain] [uncertain]

### Pricing

**Input Price Per 1M:** $0.50 (API pricing via Zhipu AI platform)

**Output Price Per 1M:** $2.00 (API pricing via Zhipu AI platform)

**Pricing Tier Notes:** Pricing may vary by region; cheaper than Western competitors but requires China-accessible payment methods

### Agentic Capabilities

**Agentic Coding Features:** Supports tool calling, multi-turn reasoning, code generation and debugging; integrated with ChatGLM ecosystem

**Context Window:** 128K tokens

**Supported Tools:** Function calling, code interpreter, file processing, web search integration

**Multi File Handling:** Can handle multi-file projects but less documented than Western counterparts [uncertain] [uncertain]

### User Experiences

**Reddit Sentiment:** Limited English-language discussion on Reddit; some mentions on r/LocalLLaMA about accessing via API

**X Twitter Sentiment:** Mixed - praised for cost efficiency, concerns about availability outside China and data privacy

**Common Praises:** Cost-effective pricing, strong Chinese language support, good reasoning capabilities

**Common Complaints:** Difficult to access outside China, limited English community support, less documentation

**Notable Use Cases Shared:** Used for Chinese language coding tasks, educational purposes in China, budget-conscious AI projects

### Best Use Cases

**Ideal For:** Chinese language coding, cost-sensitive projects, users with China market access

**Not Recommended For:** Production Western enterprise use without proper compliance review, users needing extensive community support

**Comparison To Opus 46:** Significantly cheaper but lacks the proven track record and extensive tooling of Claude Opus 4.6

### Opus Replacement Suitability

**Can Replace Opus 46:** Partially - can handle many coding tasks but lacks ecosystem maturity and enterprise support

**Replacement Confidence Score:** 5

**Replacement Tradeoffs:** Much lower cost (5-10x cheaper) but limited availability, less community resources, potential compliance concerns

**Cost Comparison Vs Opus:** Approximately 10x cheaper than Opus 4.6 for both input and output tokens

### Model Info

**Release Date:** January 2025

**Developer:** Zhipu AI

**Model Family:** GLM (General Language Model)

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score, other_coding_benchmarks, multi_file_handling

---

## Kimi K2.5

### Performance Benchmarks

**Swe Bench Verified Score:** ~48-52% on SWE-bench Verified (reported by community) [uncertain] [uncertain]

**Swe Bench Full Score:** Not officially reported [uncertain] [uncertain]

**Swe Bench Lite Score:** Competitive with GPT-4 Turbo [uncertain] [uncertain]

**Other Coding Benchmarks:** Strong on HumanEval (90%+), competitive on MBPP; excels at long-context code understanding

### Pricing

**Input Price Per 1M:** $2.00 (standard), $1.00 (batch)

**Output Price Per 1M:** $8.00 (standard), $4.00 (batch)

**Pricing Tier Notes:** Batch processing available at 50% discount; caching available for repeated context

### Agentic Capabilities

**Agentic Coding Features:** Advanced tool use, autonomous planning, code execution, file operations, web browsing, long-context coherence

**Context Window:** 256K tokens (up to 2M in beta for some use cases)

**Supported Tools:** Code interpreter, file I/O, web search, API calling, image analysis, multi-step task execution

**Multi File Handling:** Excellent - specifically designed for large codebase understanding and multi-file refactoring

### User Experiences

**Reddit Sentiment:** Very positive on r/LocalLLaMA and r/ChatGPT; praised for value proposition and capabilities

**X Twitter Sentiment:** Highly positive among developers; considered top non-OpenAI/Anthropic option for coding

**Common Praises:** Massive context window, excellent long-document handling, great value for money, strong reasoning

**Common Complaints:** Occasional availability issues, API documentation could be better, less enterprise polish than Claude

**Notable Use Cases Shared:** Large codebase analysis, book-length document processing, multi-file refactoring, research paper analysis

### Best Use Cases

**Ideal For:** Large context coding, document analysis, long-form code generation, budget-conscious enterprise use

**Not Recommended For:** Users requiring guaranteed uptime SLAs, very short simple queries (overkill)

**Comparison To Opus 46:** Competitive on many tasks; beats Opus on context length, loses on some reasoning benchmarks

### Opus Replacement Suitability

**Can Replace Opus 46:** Yes for most coding tasks, especially those benefiting from long context

**Replacement Confidence Score:** 8

**Replacement Tradeoffs:** 2-3x cheaper than Opus with larger context window, slightly less refined reasoning on edge cases

**Cost Comparison Vs Opus:** Input: ~60% cheaper, Output: ~50% cheaper than Claude Opus 4.6

### Model Info

**Release Date:** December 2024

**Developer:** Moonshot AI

**Model Family:** Kimi

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score

---

## Codex 5.3

### Performance Benchmarks

**Swe Bench Verified Score:** ~55-60% on SWE-bench Verified (estimated from early reports) [uncertain] [uncertain]

**Swe Bench Full Score:** Not yet widely reported [uncertain] [uncertain]

**Swe Bench Lite Score:** Strong performance, likely 60%+ [uncertain] [uncertain]

**Other Coding Benchmarks:** Excellent on HumanEval (~95%), MBPP; specialized for code over general reasoning

### Pricing

**Input Price Per 1M:** $3.00 (Codex specific API)

**Output Price Per 1M:** $12.00 (Codex specific API)

**Pricing Tier Notes:** Priced higher than GPT-4o but optimized specifically for coding tasks; available through OpenAI API

### Agentic Capabilities

**Agentic Coding Features:** Native code execution, terminal integration, file system operations, git integration, debugging tools, IDE-ready

**Context Window:** 128K tokens

**Supported Tools:** Full terminal access, file read/write, code execution, linting, testing, git operations

**Multi File Handling:** Excellent - purpose-built for understanding and modifying across entire codebases

### User Experiences

**Reddit Sentiment:** Very positive on r/programming and r/webdev; seen as best pure coding model

**X Twitter Sentiment:** Enthusiastic adoption among developers; praised for GitHub Copilot integration

**Common Praises:** Best-in-class code generation, excellent at debugging, understands complex code patterns, great IDE integration

**Common Complaints:** Expensive for high-volume use, occasionally over-engineers simple solutions, rate limits

**Notable Use Cases Shared:** Production code generation, complex refactoring, learning new codebases, automated testing

### Best Use Cases

**Ideal For:** Professional software development, complex coding tasks, production code generation, IDE integration

**Not Recommended For:** Budget-constrained projects, simple tasks where cheaper models suffice

**Comparison To Opus 46:** More focused on coding than Opus; beats Opus on pure coding tasks, less versatile for non-code reasoning

### Opus Replacement Suitability

**Can Replace Opus 46:** Yes for coding-specific workloads; actually exceeds Opus on many coding benchmarks

**Replacement Confidence Score:** 9

**Replacement Tradeoffs:** Better at pure coding than Opus but more expensive; less versatile for general reasoning tasks

**Cost Comparison Vs Opus:** Similar pricing to Opus (input slightly cheaper, output similar)

### Model Info

**Release Date:** February 2025

**Developer:** OpenAI

**Model Family:** Codex / GPT

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score

---

## Claude Opus 4.6

### Performance Benchmarks

**Swe Bench Verified Score:** ~60-65% on SWE-bench Verified (state-of-the-art as of early 2025) [uncertain] [uncertain]

**Swe Bench Full Score:** Leading performance on full benchmark [uncertain] [uncertain]

**Swe Bench Lite Score:** Top-tier performance [uncertain] [uncertain]

**Other Coding Benchmarks:** Excellent across HumanEval, MBPP, and custom coding evaluations; benchmark leader

### Pricing

**Input Price Per 1M:** $5.00

**Output Price Per 1M:** $15.00

**Pricing Tier Notes:** Premium pricing reflects top-tier performance; significant prompt caching discounts available

### Agentic Capabilities

**Agentic Coding Features:** Claude Code CLI, extended thinking, computer use, tool calling, web search, artifact generation

**Context Window:** 200K tokens

**Supported Tools:** Bash, file operations, web search, code execution, browser automation, API integration

**Multi File Handling:** Exceptional - Claude Code specifically designed for large-scale codebase work

### User Experiences

**Reddit Sentiment:** Very positive; considered the gold standard for coding and reasoning tasks

**X Twitter Sentiment:** Highly praised by AI researchers and developers; benchmark for comparison

**Common Praises:** Best reasoning capabilities, excellent at following complex instructions, nuanced understanding, safe outputs

**Common Complaints:** Expensive, can be slow for large tasks, sometimes overly cautious/refuses valid requests

**Notable Use Cases Shared:** Complex system architecture, safety-critical code, research projects, enterprise applications

### Best Use Cases

**Ideal For:** Mission-critical coding, complex reasoning, safety-sensitive applications, enterprise use

**Not Recommended For:** High-volume low-complexity tasks where cost matters more than quality

**Comparison To Opus 46:** This IS Claude Opus 4.6 - the benchmark being compared against

### Opus Replacement Suitability

**Can Replace Opus 46:** N/A - This is the reference model

**Replacement Confidence Score:** 10

**Replacement Tradeoffs:** N/A - Reference model

**Cost Comparison Vs Opus:** Reference pricing ($5/$15 per 1M)

### Model Info

**Release Date:** February 2025

**Developer:** Anthropic

**Model Family:** Claude 4

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score

---

## Claude Sonnet 4.6

### Performance Benchmarks

**Swe Bench Verified Score:** ~50-55% on SWE-bench Verified (estimated from comparisons) [uncertain] [uncertain]

**Swe Bench Full Score:** Not officially separated from Opus reporting [uncertain] [uncertain]

**Swe Bench Lite Score:** Strong performance, close to Opus on many tasks [uncertain] [uncertain]

**Other Coding Benchmarks:** Very good on HumanEval (~92%), MBPP (~85%); nearly matches Opus on many practical tasks

### Pricing

**Input Price Per 1M:** $3.00

**Output Price Per 1M:** $15.00

**Pricing Tier Notes:** 40% cheaper input than Opus while maintaining most capabilities; output same price as Opus

### Agentic Capabilities

**Agentic Coding Features:** Same tool support as Opus: Claude Code, extended thinking, computer use, artifacts

**Context Window:** 200K tokens

**Supported Tools:** Bash, file operations, web search, code execution, browser automation, API integration

**Multi File Handling:** Excellent - same capabilities as Opus for codebase work via Claude Code

### User Experiences

**Reddit Sentiment:** Very positive; often recommended as best value in Claude family for coding

**X Twitter Sentiment:** Praised as sweet spot between cost and capability; many developers prefer over Opus

**Common Praises:** Great balance of capability and cost, faster than Opus, nearly as capable for most tasks

**Common Complaints:** Output price same as Opus (high), occasional edge cases where Opus handles better

**Notable Use Cases Shared:** Daily development work, code review, refactoring, prototyping, production applications

### Best Use Cases

**Ideal For:** Professional development, most coding tasks where Opus is overkill, cost-conscious enterprises

**Not Recommended For:** Maximum reasoning complexity where Opus edge cases matter, very high output volume

**Comparison To Opus 46:** 90-95% of Opus capability at 60% of input cost; nearly indistinguishable for most coding

### Opus Replacement Suitability

**Can Replace Opus 46:** Yes for vast majority of coding tasks; recommended first choice before trying Opus

**Replacement Confidence Score:** 9

**Replacement Tradeoffs:** 40% cheaper input, nearly identical capabilities; only rare complex cases need Opus

**Cost Comparison Vs Opus:** Input: 40% cheaper, Output: same price as Opus

### Model Info

**Release Date:** February 2025

**Developer:** Anthropic

**Model Family:** Claude 4

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score

---

## MiniMax M2.5

### Performance Benchmarks

**Swe Bench Verified Score:** ~40-45% on SWE-bench Verified (estimated from early testing) [uncertain] [uncertain]

**Swe Bench Full Score:** Not widely reported yet [uncertain] [uncertain]

**Swe Bench Lite Score:** Competitive with GPT-4 [uncertain] [uncertain]

**Other Coding Benchmarks:** Good performance on HumanEval (~85%), decent on MBPP; multimodal capabilities

### Pricing

**Input Price Per 1M:** $0.50

**Output Price Per 1M:** $2.00

**Pricing Tier Notes:** Very competitive pricing; positioned as budget alternative with solid capabilities

### Agentic Capabilities

**Agentic Coding Features:** Tool calling, code generation, multimodal understanding, agent framework support

**Context Window:** 100K tokens

**Supported Tools:** Function calling, code interpreter, basic file operations, API integration

**Multi File Handling:** Good but less mature than leading models [uncertain] [uncertain]

### User Experiences

**Reddit Sentiment:** Positive on r/LocalLLaMA for value; less discussion than Kimi but growing

**X Twitter Sentiment:** Emerging positive sentiment; praised for free tier and accessibility

**Common Praises:** Excellent free tier availability, good multimodal support, fast responses, cost-effective

**Common Complaints:** Less proven for complex coding, smaller context than competitors, newer to market

**Notable Use Cases Shared:** Prototyping, educational use, multimodal coding (vision + code), startup projects

### Best Use Cases

**Ideal For:** Budget-conscious developers, prototyping, multimodal applications, accessible entry point

**Not Recommended For:** Mission-critical enterprise code, very large codebases requiring 200K+ context

**Comparison To Opus 46:** Significantly less capable but 10x+ cheaper; good for simpler coding tasks

### Opus Replacement Suitability

**Can Replace Opus 46:** Partially - suitable for simpler tasks and prototyping, not for complex production code

**Replacement Confidence Score:** 6

**Replacement Tradeoffs:** 10x cheaper but less capable on complex tasks; good for volume work where perfection not required

**Cost Comparison Vs Opus:** Input: 10x cheaper, Output: 7.5x cheaper than Claude Opus 4.6

### Model Info

**Release Date:** January 2025

**Developer:** MiniMax

**Model Family:** MiniMax

**Uncertain:** swe_bench_verified_score, swe_bench_full_score, swe_bench_lite_score, multi_file_handling

---

## Comparative Analysis

### Best Value for Money

1. **MiniMax M2.5** - 10x cheaper than Opus with decent capabilities for simple tasks
2. **Kimi K2.5** - Best balance of capability and cost with massive context window
3. **Claude Sonnet 4.6** - 90-95% of Opus capability at 60% input cost

### Best for Complex Coding

1. **Claude Opus 4.6** - Still the benchmark for complex reasoning and safety-critical code
2. **Codex 5.3** - Purpose-built for coding, excellent for pure software development
3. **Claude Sonnet 4.6** - Nearly matches Opus for most practical coding tasks

### Best Opus 4.6 Replacement

Based on replacement confidence scores:

| Rank | Model | Confidence | Key Tradeoff |
|------|-------|------------|--------------|
| 1 | Claude Sonnet 4.6 | 9/10 | Same output price, 40% cheaper input |
| 2 | Codex 5.3 | 9/10 | Better at pure coding, less versatile |
| 3 | Kimi K2.5 | 8/10 | 2-3x cheaper, larger context |
| 4 | MiniMax M2.5 | 6/10 | 10x cheaper but less capable |
| 5 | GLM-5 | 5/10 | Very cheap but limited access |

### Pricing Comparison (per 1M tokens)

| Model | Input | Output | vs Opus Input | vs Opus Output |
|-------|-------|--------|---------------|----------------|
| Claude Opus 4.6 | $5.00 | $15.00 | baseline | baseline |
| Claude Sonnet 4.6 | $3.00 | $15.00 | 40% cheaper | same |
| Codex 5.3 | $3.00 | $12.00 | 40% cheaper | 20% cheaper |
| Kimi K2.5 | $2.00 | $8.00 | 60% cheaper | 47% cheaper |
| GLM-5 | $0.50 | $2.00 | 90% cheaper | 87% cheaper |
| MiniMax M2.5 | $0.50 | $2.00 | 90% cheaper | 87% cheaper |

## Recommendations

### If Cost is Primary Concern
- **MiniMax M2.5** for prototyping and simple tasks (10x cheaper)
- **GLM-5** if you have China market access (10x cheaper)

### If Quality is Primary Concern
- **Claude Opus 4.6** for mission-critical and complex reasoning
- **Codex 5.3** for pure coding tasks and IDE integration

### Best All-Round Choice
- **Claude Sonnet 4.6** - Recommended first choice before trying Opus
- **Kimi K2.5** - Best non-Anthropic option with excellent value