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GLM 5.2 Alternatives: 6 Open-Weight Coding Models
GLM 5.2 alternatives, ranked: 6 open-weight coding models from DeepSeek V4 to Kimi & MiniMax—how each compares, and when GLM 5.2 is still the best pick.
GLM 5.2 Benchmarks: How It Really Performs
GLM 5.2 benchmarks decoded: 62.1 on SWE-bench Pro, 74.4 on FrontierSWE—beating GPT-5.5 and chasing Opus 4.8 at a fraction of the cost. See what the scores mean.
GLM 5.2 vs Claude Opus 4.8: Coding, Compared
GLM 5.2 vs Claude Opus 4.8—which really wins for coding? Both tested on 40 real PRs: benchmarks, 1M context, open weights. See the verdict and try GLM 5.2 free.
GLM 5.2 vs Claude Sonnet 5: Cost, Benchmarks, and Open vs Closed
Claude Sonnet 5 costs $15/M output tokens versus GLM 5.2's $4.40 — 3.4× more expensive. Sonnet 5 leads on reasoning and coding benchmarks, but GLM 5.2 offers MIT open weights and 1M-token context at significantly lower cost.
GLM 5.2 vs DeepSeek V3: Benchmarks, Pricing, and Use Cases
DeepSeek V3 costs 75% less per output token than GLM 5.2 but scores 4 points lower on the AA Intelligence Index and has 8x less context. Here is when each model is the right call.
GLM 5.2 vs Fable 5: Open Source vs Closed
GLM 5.2 ranks #1 on Design Arena (Elo 1360) and costs 7× less than Fable 5. Fable 5 leads on vision tasks. Benchmark table, pricing, and a decision guide inside.
GLM 5.2 vs Gemini 2.5 Flash: Cost, Speed, and Benchmark Comparison
Gemini 2.5 Flash costs $0.30/M output tokens versus GLM 5.2's $4.40 — 15× cheaper. Flash is optimized for high-volume tasks. GLM 5.2 scores higher on complex coding and offers open weights. Here is when each model is the right call.
GLM 5.2 vs Gemini 2.5 Pro: Performance, Price, and When to Choose Each
Gemini 2.5 Pro scores ~75 on the AA Intelligence Index versus GLM 5.2's 51, but output tokens cost 2.3x more and it is closed source. GLM 5.2 is 3x faster. Here is the full breakdown.
GLM 5.2 vs GLM-4: What Changed and Whether the Upgrade Is Worth It
GLM 5.2 has 753B parameters versus GLM-4's 9B-130B range, scores significantly higher on reasoning benchmarks, and offers 1M token context. Here is when the upgrade is worth it.
GLM 5.2 vs GPT-4.1: Benchmarks, Pricing, and When to Choose
GPT-4.1 costs $8/M output tokens versus GLM 5.2's $4.40 — 82% more expensive. GPT-4.1 improves on instruction following and long-context coding, but GLM 5.2 delivers MIT open weights at significantly lower cost for comparable software engineering tasks.
GLM 5.2 vs GPT-4o: Benchmarks, Pricing, and the Real Cost Difference
GLM 5.2 costs 56% less per output token than GPT-4o and runs 3× faster, but GPT-4o adds audio and multimodal input that GLM 5.2 doesn't support. Here's when each model is the right call.
GLM 5.2 vs GPT-5.6 Sol: Benchmarks, Pricing, and the 6.8× Cost Gap
GPT-5.6 Sol costs $30/M output tokens versus GLM 5.2's $4.40 — 6.8× more expensive. Sol leads on reasoning benchmarks, but both score within 2.5 points on SWE-bench Pro. Here's when each model is worth the premium.
GLM 5.2 vs Grok 3: Speed, Pricing, and Benchmark Comparison
Grok 3 scores ~68 on the AA Intelligence Index versus GLM 5.2's 51, but output tokens cost 3.4x more and responses arrive 3x slower. Here is when each model is worth it.
GLM 5.2 vs Claude Haiku 4.5: Speed, Cost, and When Size Matters
Claude Haiku 4.5 costs $4/M output tokens — nearly the same as GLM 5.2's $4.40. But Haiku 4.5 is optimized for speed on simple tasks, while GLM 5.2 excels at complex coding with 1M-token context.
GLM 5.2 vs Kimi K2.5: Benchmarks, Pricing, and When to Choose Each
GLM 5.2 scores 51 on intelligence vs Kimi K2.5's 35, runs 3x faster, and has a 4x larger context window — but Kimi K2.5 is 57% cheaper and supports image and video input.
GLM 5.2 vs Kimi K3: Benchmarks, Pricing, and Which One to Use
Kimi K3 scores 57 on the AA Intelligence Index versus GLM 5.2's 51, but output tokens cost 3.4× more and responses arrive 2.5× slower. Here's when each model is worth it.
GLM 5.2 vs Llama 3.3 70B: Open-Weight Models Compared on Speed, Benchmarks, and Cost
Llama 3.3 70B costs 80% less via Groq than GLM 5.2 direct but scores 9 points lower on the AA Index and has 8x less context. Here is which open-weight model fits your workload.
GLM 5.2 vs Mistral Large 2: Benchmarks, Cost, and Enterprise Fit
Mistral Large 2 costs $6.00/M output tokens versus GLM 5.2's $4.40 and scores lower on most benchmarks. GLM 5.2 also has 8x larger context and MIT-open weights. Here is the full comparison.
GLM 5.2 vs Phi-4: Frontier Scale vs Efficient Small Model
Phi-4 is a 14B-parameter model that runs on a single GPU. GLM 5.2 is a 753B MoE model with 1M-token context and frontier coding benchmarks. Here is when each is the right tool.
GLM 5.2 vs Qwen 3: Chinese Open-Weight AI Models Compared
Qwen 3 235B-A22B costs 73% less per output token than GLM 5.2, but GLM 5.2 has 8x larger context and stronger agentic benchmark results. Here is how these open-weight leaders compare.
Kimi K3 vs Claude Opus 4.8: Frontier Models Head-to-Head
Claude Opus 4.8 costs $75/M output tokens versus Kimi K3's $15/M — 5× more expensive. Opus 4.8 leads every benchmark and sets the bar for top-tier AI. Here is when the premium is justified.
Kimi K3 vs DeepSeek V3: Cost, Speed, and Coding Benchmarks
DeepSeek V3 costs $1.10/M output tokens versus Kimi K3's $15/M — 13× cheaper. Kimi K3 scores ~10 points higher on the AA Intelligence Index. Here is when each open-weight-adjacent model is the right call.
Kimi K3 vs Gemini 2.5 Pro: Performance, Price, and Context Window
Gemini 2.5 Pro scores significantly higher on the AA Intelligence Index than Kimi K3 and costs $10/M output tokens versus K3's $15/M — 33% cheaper for a stronger model. Here is how these 1M-context models compare.
Kimi K3 vs GPT-4o: Benchmarks, Speed, and When to Choose Each
Kimi K3 and GPT-4o both score around 57 on the AA Intelligence Index but take opposite positions on cost and context. K3 output tokens cost 50% more; GPT-4o has audio input but only 128K context.