Configure Your AI Agent
With The Right LLM
Every AI agent task demands different strengths - raw coding power, autonomous CLI execution, deep reasoning, or maximum context. Match your workload to the best model with real benchmark data, live cost estimates, and task-specific recommendations.
Find Your AI Model
Pick your task profile and see which models score highest based on weighted benchmark matching. Adjust session parameters to estimate real-world costs.
Hermes Agent
Hermes needs reliable tool calling, large context (memory + conversation), and prompt caching for long sessions. DeepSeek V4 Pro is the default.
Top Recommendations for Hermes Agent
V4 Pro
1.6T MoE with 49B active per token. MIT open-source. 1M context with hybrid attention (CSA+HCA). State-of-the-art competitive coding and math reasoning at 7-9x lower cost than frontier models.
MiniMax M3
Open-weight surprise. 92.68% GPQA Diamond, 80.5% SWE-bench Verified. 1M context. Very strong reasoning at $0.30-$0.60 input. Best value open-weight model.
V4 Flash
284B MoE with 13B active per token. MIT open-source. Ultra-cheap at $0.14/$0.28 per MTok. 1M context. Perfect for high-volume, cost-sensitive production workloads.
All Models Ranked
| Rank | Model | Score | Session Cost | Input $ | Output $ |
|---|---|---|---|---|---|
| 1 | V4 Pro DeepSeek | 99% | $0.057 | $0.43 | $0.87 |
| 2 | MiniMax M3 MiniMax | 98% | $0.099 | $0.45 | $1.80 |
| 3 | V4 Flash DeepSeek | 96% | $0.018 | $0.14 | $0.28 |
| 4 | Sonnet 4.6 Anthropic | 78% | $0.900 | $3.00 | $15.00 |
| 5 | Kimi K2.6 Moonshot AI | 73% | $0.260 | $1.00 | $4.00 |
| 6 | Gemini 3.1 Pro Google | 72% | $0.680 | $2.00 | $12.00 |
| 7 | Opus 4.8 Anthropic | 62% | $1.500 | $5.00 | $25.00 |
| 8 | GPT 5.3 Codex OpenAI | 60% | $0.656 | $1.75 | $14.00 |
| 9 | Haiku 4.5 Anthropic | 54% | $0.300 | $1.00 | $5.00 |
| 10 | GPT-5.5 OpenAI | 46% | $1.575 | $5.00 | $30.00 |
| 11 | GPT-5.4 OpenAI | 36% | $0.738 | $2.50 | $15.00 |
| 12 | Fable 5 Anthropic | 32% | $3.000 | $10.00 | $50.00 |
AI Model Benchmark Comparison
Side-by-side comparison of every frontier model across SWE-bench Verified, SWE-bench Pro, Terminal-Bench 2.0, GPQA Diamond, and MMLU-Pro. Sort by any column. Click any row for full details.
| Open | ||||||||
|---|---|---|---|---|---|---|---|---|
| 1.0M | 95.0% | 80.3% | — | — | — | $10.00/$50.00 | ||
| 1.0M | 88.6% | 69.2% | — | 93.6% | 89.1% | $5.00/$25.00 | ||
| 1.0M | 80.6% | 55.4% | 67.9% | 90.1% | 87.5% | $0.43/$0.87 | ||
| 1.0M | 80.6% | 54.2% | — | 94.3% | 92.6% | $2.00/$12.00 | ||
| 1.0M | 80.5% | — | 66.0% | 92.7% | 84.2% | $0.45/$1.80 | ||
| 256K | 80.2% | — | 66.7% | — | — | $1.00/$4.00 | ||
| 1.0M | 79.6% | — | 42.8% | 82.0% | 84.6% | $3.00/$15.00 | ||
| 1.0M | 79.0% | — | 56.9% | 88.1% | 86.2% | $0.14/$0.28 | ||
| 200K | 73.3% | 39.5% | — | — | — | $1.00/$5.00 | ||
| 400K | — | 58.6% | 82.7% | — | — | $5.00/$30.00 | ||
| 400K | — | — | 77.3% | — | — | $1.75/$14.00 | ||
| 400K | — | 51.9% | — | — | — | $2.50/$15.00 |
Data sourced from vendor reports, SWE-bench leaderboard, and third-party benchmarks as of June 17, 2026. Click a row for full details.
Cost Calculator
Pick two models and see exactly how much you'd save per session, per month, and per year. Adjust turns, token counts, and session frequency to match your workload.
How We Score Models
SWE-bench Verified
weight: 0-40%Real-world GitHub issues. Models fix actual bugs in Python repos using a standardized scaffold. The best predictor of production coding ability.
Terminal-Bench 2.0
weight: 0-40%Autonomous CLI agent tasks. Models navigate file systems, run builds, orchestrate shell commands - measures true agent autonomy.
GPQA Diamond
weight: 0-40%Expert-level science questions (PhD-level biology, physics, chemistry). Measures deep reasoning ability beyond surface pattern matching.
MMLU-Pro
weight: 0-30%Massive multitask language understanding - 57 subjects across STEM, humanities, and social sciences. Broad knowledge benchmark.
Data sourced from SWE-bench leaderboard, vendor technical reports (DeepSeek, Anthropic, OpenAI), Artificial Analysis, and third-party evaluators. Artificial Analysis, and third-party evaluators. Last updated June 17, 2026. Pricing verified against official API documentation.
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