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Finding the True 'King of Cost-Effectiveness'

In-depth analysis of the latest DeepSew benchmark data: Under the premise of meeting the performance baseline, using absolute low price as the highest standard, revealing gpt-5.6-luna as the true king of cost-effectiveness today.

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Finding the True 'King of Cost-Effectiveness'

In the recently released DeepSew (Note: Code/Agent capabilities) benchmark leaderboard, the comprehensive performance (Pass@1 success rate), average cost (Avg Cost), output tokens, and interaction steps of major mainstream models have been fully disclosed.

In actual large-scale commercial deployments and daily development assistance, we often follow a strict principle: once the model capabilities cross the business-usable performance baseline, invocation cost becomes the sole dimension for measuring cost-effectiveness. Based on this standard, we reshuffle the deck to reveal who is truly the current "King of Cost-Effectiveness".

📊 Core Benchmark Data at a Glance

ModelSuccess Rate (Pass@1)Avg CostTokens ConsumedSteps
gpt-5.6-sol73%$8.3960k61
claude-fable-570%$21.63119k88
gpt-5.6-terra70%$4.9572k76
gpt-5.6-luna67%$3.0373k102
gpt-5.567%$7.2346k82
claude-opus-4.859%$13.22135k120
claude-sonnet-554%$26.40214k268
gpt-5.452%$5.6571k70
glm-5.244%$3.9278k129
gemini-3.5-flash37%$7.34276k86
kimi-k2.7-code31%$2.8259k149

🏆 Performance & Cost-Effectiveness Analysis (Cost-Driven)

We consider a Pass@1 rate of 65% and above as the dividing line for "highly usable". Among all the models that cross this performance baseline, we let them fight directly on cost.

1. 👑 The True King of Cost-Effectiveness: gpt-5.6-luna

If price is the only standard, then gpt-5.6-luna is the undisputed king. It boasts an excellent 67% accuracy rate (perfectly tying the previous flagship gpt-5.5), but its single-call cost has been compressed to the extreme at $3.03. Compared to the absolute cheapest across the board, kimi-k2.7-code ($2.82), luna requires only a minor cost increase to pull the success rate from an unusable 31% up to 67%. For the vast majority of tasks, it is the most economical choice for productivity.

2. Upgraded High-Quality Choice: gpt-5.6-terra

If your tasks are more demanding and 67% is not enough, the next tier choice is gpt-5.6-terra. It reaches an extremely high accuracy of 70% while costing only $4.95. Although slightly more expensive than luna, compared to claude-fable-5 which offers the same 70% accuracy (but at a whopping $21.63), terra's price advantage remains dominant.

3. Budget-Insensitive Absolute King: gpt-5.6-sol

If the business scenario requires the best possible outcome for every request, call gpt-5.6-sol directly. With the overall highest success rate of 73%, the fewest interaction steps (61), its $8.39 cost is well worth it for top-tier complex problems.

Under the perspective of "meeting the baseline and cost-driven", some models reveal extremely poor ROI:

  • gpt-5.5: Offers the same 67% accuracy as luna, but costs up to $7.23 (1.3 times more expensive). It belongs to a bygone era and should be directly replaced.
  • Claude Series: Shows a tendency of "high price, low configuration" across the board. claude-fable-5 (70%) requires $21.63, and claude-sonnet-5 demands a field-topping $26.40 for a mere 54% accuracy—a true "API bill assassin".

💡 Summary

  • Daily/High-Frequency Calls: No-brainer choice: gpt-5.6-luna ($3.03 / 67%).
  • Complex Task Balance Point: Choose gpt-5.6-terra ($4.95 / 70%).
  • Core Breakthroughs: Choose gpt-5.6-sol ($8.39 / 73%).

In today's highly competitive model landscape, adhering to the principle of "looking at quality below the baseline, and comparing cost above the baseline" can save massive API expenses for enterprises.

(Data source: deepsew latest model benchmark results)

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