Why a Three-Way Grid Beats Pairs for open-source LLM picks
TokenRate's new Compare Prices grid puts every model's per-token rates, context window, and quality score in a single side-by-side view. The point: stop flipping between provider pricing pages and OpenRouter tabs. You pick a provider dropdown, check the models you want, repeat for each provider, and the grid stacks every pick into one comparison table. A two-model comparison answers "which of these wins," but it doesn't catch the third option that quietly dominates both — and that's a common case for open-source LLM picks. This guide grids **Llama 4 Maverick**, **DeepSeek V3**, and **Mistral Large** in /tools/compare-prices so you can see all three side-by-side: input rates, output rates, context windows, and quality scores in stacked columns. The trio was picked because each represents a different point on the quality-vs-price curve — DeepSeek V3 at the budget end, Llama 4 Maverick at the quality end, and DeepSeek V3 winning the Value column with 240.7 (quality ÷ input cost). Related reading: quality per dollar LLM ranking 2026, LLM color-coded quality badges explained, and why the cheapest LLM isn't always the best value.
Building the Grid: Provider Dropdowns and Picks
Open /tools/compare-prices. Tick **Llama 4 Maverick** in the **Meta** dropdown, **DeepSeek V3** in the **DeepSeek** dropdown, and **Mistral Large** in the **Mistral** dropdown. The grid stacks them with input cost / output cost / context / quality in one row each. Llama 4 Maverick: $0.500 in, $1.50 out, 1M ctx, Q70. DeepSeek V3: $0.270 in, $1.10 out, 64K ctx, Q65. Mistral Large: $2.00 in, $6.00 out, 128K ctx, Q66. The model ID column (visible on hover) is the string you paste into your SDK call.
Reading the Cost Spread
Input cost spans $0.270 to $0.500 — a 7.4× spread. Output cost matters more than input when reply length exceeds prompt length (typical for content generation, agents, code). Output-to-input ratios: Llama 4 Maverick 3.0×, DeepSeek V3 4.1×, Mistral Large 3.0×. The model with the lowest output ratio tends to be the cheapest for generation-heavy workloads, regardless of input rate. For a workload mix calculator that bakes in your specific in/out ratio, run the same models through /tools/api-cost-estimator.
Quality and Value Tradeoffs
**Llama 4 Maverick** leads on quality (70). **DeepSeek V3** leads on raw cost ($0.270/1M input). **DeepSeek V3** leads on the Value column (240.7) — meaning the highest quality-adjusted return per dollar. In practice, this means: when accuracy is non-negotiable, pay for Llama 4 Maverick; when budget is the binding constraint and quality just needs to clear a floor, ship DeepSeek V3; when you want the best default for production routing, DeepSeek V3 is the answer. For the methodology behind that Value formula, see Value column vs tokens per dollar and quality per dollar LLM ranking 2026.
Workflow: From Grid to Production Decision
Once the trio is on screen, the workflow is: (1) eliminate any model whose quality is below the floor your workload tolerates — score < 50 for customer-facing, < 65 for reasoning-heavy. (2) of the survivors, compare Value column rankings. (3) for the top one or two, estimate monthly bill via /tools/api-cost-estimator using your expected token volume. (4) ship a 1-week A/B with Llama 4 Maverick as the gold-standard control and your Value pick as the candidate. The Compare Prices grid is the first step in that funnel — it eliminates the wrong picks fast. Both the price denominator (OpenRouter) and the quality numerator (Arena AI + Artificial Analysis) refresh hourly. So the comparison you screenshot Monday morning is still trustworthy at standup Tuesday morning — but you should re-run it before a quarterly model-routing review. Open /tools/compare-prices now, pick your provider dropdowns, and pin the shortlist that matches your workload.