AI Agent Store/Model comparisonsBuild an AI worker ↗THE MODEL SELECTION SERIES
Open weights are downloadable files containing a trained model, available under its license. That can create more deployment options, but it does not automatically make a model free to run, fully open source or unrestricted for commercial use.
Data reviewed · LiveBench question set: 25 June 2026 · View every source ↗ · Download the data ↓
The comparison uses hosted API prices and advertised endpoint context limits. It does not estimate the GPU memory, utilization, networking or operations cost of self-hosting. The same weights can behave differently when compressed to use less memory or run with different software.
Review redistribution, commercial-use and acceptable-use conditions on the model’s own release page. A family name is not enough: parameter count, version, quantization and thinking settings can all change the comparison.
A provider advertising tool support does not guarantee your local server implements the same protocol. Check that answers follow your required format, multiple tool calls work, errors are handled and input limits are respected with the deployment you plan to use.
Hosted prices are a useful starting point. For self-hosting, calculate utilization and total monthly infrastructure cost, including idle capacity and operational time. Benchmark throughput on your actual hardware before treating a theoretical token price as achievable.
The comparison starts with open-weight models. Prices represent hosted API endpoints; check the model license before self-hosting.
YOUR WORKLOAD. YOUR PRIORITIES.
Tokens are the small pieces of text a model reads or produces. Include charged thinking tokens in output.
This estimate uses your token counts and standard text API rates. It excludes cache discounts, tool fees, retries and provider premiums. If your input and output exceed a model’s listed capacity, we leave its cost and Value rating blank. A large capacity does not guarantee that it will use every detail correctly.
Shaded zone: 73.5+ points and $10.58 or less. Numbers mark models with strong price–quality tradeoffs in or near this zone. On the dotted line, no other shown model is cheaper with an equal or higher score, or scores higher at the same price. Your chosen measure, usage and filters change this shortlist.
Practical Value · General agent
70% Agent Fit + 30% affordability. Rankings use your workload. Filtering the list does not change how scores are calculated.
THE EVIDENCE, SIDE BY SIDE
DeepSeek · max
Moonshot AI · source default
Alibaba · source default
DeepSeek · experimental · source default
Z.ai · source default
Alibaba · source default
DeepSeek · source default
DeepSeek · source default
Thinking Machines · xhigh
Z.ai · source default
Z.ai · source default
DeepSeek · source default
| Compare | Input / outputUSD / 1M tokens | ||||||||
|---|---|---|---|---|---|---|---|---|---|
01 DeepSeek V4.1 Flash ↗DeepSeek · maxOpen weights | 78.9 | 84.2 | — | 81.1 | — | $1.94 | 1.05M | $0.0158 / $0.891OpenRouter catalog | |
02 Kimi K3 ↗Moonshot AI · source defaultOpen weights | 77.4 | 65.6 | — | 79.2 | — | $35 | 1.05M | $0.5 / $15OpenRouter catalog | |
03 Qwen3.8 Flash Next ↗Alibaba · source defaultOpen weights | 76.2 | — | — | 76.2 | — | — | Not verified | Not verified | |
04 DeepSeek V4 Flash Vision Exp ↗DeepSeek · experimental · source defaultOpen weightsPreview | 75.1 | 79.5 | — | 76.8 | — | $3.45 | 1.05M | $0.2156 / $0.6468OpenRouter catalog | |
05 GLM-5.3 ↗Z.ai · source defaultOpen weights | 73.7 | 73.8 | — | 76.1 | — | $10.6 | 1.05M | $0.1 / $4.8OpenRouter catalog | |
06 Qwen3.8 27B ↗Alibaba · source defaultOpen weights | 73.5 | 76.3 | — | 75.3 | — | $6.8 | 1.00M | $0.24 / $2.2OpenRouter catalog | |
07 DeepSeek V4 Pro 0813 ↗DeepSeek · source defaultOpen weights | 73.3 | 74.0 | — | 77.4 | — | $10.56 | 1.05M | $0.66 / $1.98OpenRouter catalog | |
08 DeepSeek V4 Flash 0731 ↗DeepSeek · source defaultOpen weights | 71.1 | 79.3 | — | 74.2 | — | $1.44 | 1.05M | $0.016 / $0.64OpenRouter catalog | |
09 Inkling ↗Thinking Machines · xhighOpen weights | 68.9 | 64.3 | — | 71.9 | — | $18.1 | 524K | $1 / $4.05OpenRouter catalog | |
10 GLM-5.2 ↗Z.ai · source defaultOpen weights | 68.5 | 67.1 | — | 73.2 | — | $14.4 | 1.05M | $0.04 / $7OpenRouter catalog | |
11 GLM-5.3 Flash ↗Z.ai · source defaultOpen weights | 67.2 | 74.5 | — | 71.6 | — | $2.5 | 1.05M | $0.15 / $0.5OpenRouter catalog | |
12 DeepSeek V4 Pro ↗DeepSeek · source defaultOpen weights | 67.1 | 67.1 | — | 71.6 | — | $13.37 | 1.05M | $0.9553 / $1.91OpenRouter catalog | |
13 Kimi K2.6 ↗Moonshot AI · thinkingOpen weights | 66.9 | 67.5 | — | 70.5 | — | $13.32 | 262K | $0.65 / $3.41OpenRouter catalog | |
14 Kimi K2.7 Code ↗Moonshot AI · source defaultOpen weights | 64.8 | 65.0 | — | 68.4 | — | $13.41 | 262K | $0.6712 / $3.35OpenRouter catalog | |
15 Nemotron 3 Ultra ↗NVIDIA · 550B A55B · source defaultOpen weights | 63.8 | 66.4 | — | 67.4 | — | $10.8 | 262K | $0.6 / $2.4OpenRouter catalog | |
16 DeepSeek V4 Flash ↗DeepSeek · source defaultOpen weights | 61.6 | 73.1 | — | 65.5 | — | $1.27 | 1.05M | $0.091 / $0.182OpenRouter catalog | |
17 Qwen3.6 27B ↗Alibaba · source defaultOpen weights | 60.0 | 65.3 | — | 64.0 | — | $9.6 | 262K | $0.32 / $3.2OpenRouter catalog |
— means a comparable result is unavailable. Consensus combines results for only 10 matched configurations. Model IDs, reasoning settings, source links and pricing differences are available on every model page. Downloadable model files can still have restrictions on commercial use.
LOOK BEYOND ONE NUMBER
| Measure | Claude Opus 5.5max | GPT-6 Solmax | DeepSeek V4.1 Flashmax |
|---|---|---|---|
| Agent Fit | 79.4 | 74.7 | 78.9 |
| Practical Value | 60.7 | 62.4 | 84.2 |
| Evidence Consensus | Insufficient evidence | Insufficient evidence | Insufficient evidence |
| Workload cost | $80 | $40 | $1.94 |
| Context window | 1.00M | 1.05M | 1.05M |
| Tool calling | Supported | Supported | Supported |
| Reasoning | 92.2 | 88.7 | 86.7 |
| Coding | 89.3 | 81.8 | 80.0 |
| Agentic coding | 71.7 | 52.9 | 77.3 |
| Mathematics | 97.1 | 96.4 | 93.3 |
| Data analysis | 80.3 | 81.2 | 79.3 |
| Language | 86.3 | 85.3 | 81.2 |
| Instruction following | 65.7 | 68.6 | 70.0 |
| Input / output per 1M | $4 / $20 | $2 / $10 | $0.0158 / $0.891 |