Standardized workload

What can €20 actually buy?

At the 12 Aug 2026 snapshot, standard consumer plans were close to $20 per month and some premium tiers reached $200. Prices and conditions can change; first-party plan pages are linked below.

Using the costs observed across the 60 exercises common to all configurations, we estimate how much rubric-score-equivalent workload the same budget would purchase through an API. Prices include input and billable output tokens, including reported reasoning tokens. The conversion €1 = $1.1392 is the ECB reference rate for 23 Jun 2026 ↗.

ModelMean scoreMean costExercises with €203-exercise equivalents
DeepSeek V4 Flash, no thinking86.31€0.001711,5343,844
GPT-6 Luna98.47€0.00513,8991,299
DeepSeek V4 Flash97.24€0.00563,5551,185
Mistral Small 485.57€0.00932,151717
DeepSeek V4 Pro96.71€0.01331,501500
Claude Haiku 4.564.77€0.01771,131377
DeepSeek V4.1 Flash97.23€0.0228876292
Grok 4.385.24€0.0230868289
OpenAI GPT-4.171.58€0.0331604201
Claude Sonnet 4.570.91€0.0361553184
Grok 4.594.61€0.0476420140
Claude Sonnet 5.598.67€0.0494405135
OpenAI o392.75€0.072027792
GPT-6.1 Sol99.09€0.079925083
Gemini 3.1 Pro Preview97.05€0.115417357
Gemini 3.5 Flash96.95€0.124316053
Claude Opus 5.599.11€0.128015652
Mistral Medium 3.587.07€0.129015551
Claude Fable 597.99€0.33535919
GPT-5.6 Sol98.72€0.40684916

Data & methodDownload the score-and-ranking CSV ↗ and the token-and-cost CSV ↗. Workload is calculated as budget divided by observed mean euro cost per exercise.

Gemma 4 31B IT is excluded because its benchmark campaign rate was recorded as zero, which is not a universal market price. The scale difference is striking: roughly 49 Sol exercises versus 3,555 with DeepSeek V4 Flash for 1.48 fewer mean score points.

Standardized unit. These counts do not imply a user submits only full university examinations. They provide a common unit for explanations, corrections, alternate derivations and follow-up questions.

Explore the trade-off

Set your own budget and quality threshold

The chart converts observed per-exercise API cost into theoretical workload. Change the assumptions to see which models remain economically plausible for your use case.

Interactive budget model

How much mathematical work could your budget purchase?

Monthly budget€20monthly
Monthly budget presets
Total requestsexercises · observed mean cost
DeepSeek V4 Flash (no thinking)86.31% mean score
11,534
GPT-6 Luna98.47% mean score
3,899
DeepSeek V4 Flash97.24% mean score
3,555
Mistral Small 485.57% mean score
2,151
DeepSeek V4 Pro96.71% mean score
1,501
Claude Haiku 4.564.77% mean score
1,131
DeepSeek V4.1 Flash97.23% mean score
876
Grok 4.385.24% mean score
868
OpenAI GPT-4.171.58% mean score
604
Claude Sonnet 4.570.91% mean score
553
Grok 4.594.61% mean score
420
Claude Sonnet 5.598.67% mean score
405
OpenAI o392.75% mean score
277
GPT-6.1 Sol99.09% mean score
250
Gemini 3.1 Pro Preview97.05% mean score
173
Gemini 3.5 Flash96.95% mean score
160
Claude Opus 5.599.11% mean score
156
Mistral Medium 3.587.07% mean score
155
Claude Fable 597.99% mean score
59
GPT-5.6 Sol98.72% mean score
49

The principal estimate uses observed mean cost. The thin range shows an indicative ±20% workload band—not a confidence interval—and illustrates sensitivity to problem complexity, response length and reasoning usage.

Highest observed meanClaude Opus 5.599.11%
Maximum workloadGPT-6 Luna3,899 exercises
Cheapest above thresholdGPT-6 Luna98.47% at €0.0051 per exercise
Consider the trade-off

DeepSeek V4 Flash processes approximately 72 times more requests than GPT-5.6 Sol, while its mean score is 1.48 points lower. Is that final accuracy margin worth the reduction in volume?

Price references only€20monthly standard plan€100premium plan reference€200premium plan reference€240annualized standard plan

These lines compare prices only. They do not claim that a consumer subscription provides an equivalent quantity of API usage, messages or tokens.

Data & methodThe explorer uses the same score CSV ↗ and cost CSV ↗, with the budget and minimum-score filters applied in the browser.

Annual perspective

A €20 monthly plan corresponds to €240 per year

ModelExercises with €2403-exercise equivalents
DeepSeek V4 Flash, no thinking138,41246,137
GPT-6 Luna46,79115,597
DeepSeek V4 Flash42,66314,221
Mistral Small 425,8188,606
DeepSeek V4 Pro18,0236,007
Claude Haiku 4.513,5754,525
DeepSeek V4.1 Flash10,5163,505
Grok 4.310,4193,473
OpenAI GPT-4.17,2582,419
Claude Sonnet 4.56,6392,213
Grok 4.55,0461,682
Claude Sonnet 5.54,8611,620
OpenAI o33,3331,111
GPT-6.1 Sol3,0041,001
Gemini 3.1 Pro Preview2,079693
Gemini 3.5 Flash1,930643
Claude Opus 5.51,874624
Mistral Medium 3.51,860620
Claude Fable 5715238
GPT-5.6 Sol589196

Data & methodAnnual capacity applies the same reproducible formula with a €240 budget. Inputs: historical cost CSV ↗ and the dated ECB exchange-rate source ↗.

These values describe API capacity under benchmark-like workloads. They do not imply that subscriptions permit the same volume: message limits are not expressed as equivalent API tokens and may vary by model, context length and demand.

Real workflows also include uploaded files, revisions, long conversations and verification requests. Each increases processed context and may materially raise API expenditure. The table is therefore a baseline before accounting for the wider workflow.

Reference threshold

Where is the subscription break-even point?

N* = monthly subscription price / mean API cost per exercise

At €20, API expenditure reaches the reference price after approximately 49 Sol exercises, 59 Fable exercises, 1,501 DeepSeek V4 Pro exercises or 3,555 DeepSeek V4 Flash exercises.

These thresholds show when theoretical API expenditure exceeds €20—not whether a subscription can sustain the same workload within its message, session or weekly limits.

The break-even workload differs by orders of magnitude across models. Subscription attractiveness therefore depends strongly on the API price of the underlying model and on the actual number of substantial requests made each month.

Marginal value

How much is the final percentage point worth?

GPT-5.6 Sol reaches 98.72%. DeepSeek V4 Flash reaches 97.24% while costing approximately 72 times less per exercise.

+1.48Mean score pointsSol over DeepSeek Flash
72×Higher expenditure€0.4068 versus €0.0056
3,555Flash exercisesFor the same €20 budget

Sol has the higher observed benchmark mean. Whether the additional 1.48 points justify the price depends on the cost of error, not only the cost of the request.

Is DeepSeek V4 Flash the economic optimum?

Within the common panel, Flash presents a strong observed quality–cost combination: 97.24% at approximately €0.0056 per exercise. V4 Pro costs around 2.4 times more while scoring 96.71%, so it is economically dominated on this workload. Product labels such as Pro, Max or Ultra do not guarantee a superior quality–cost relationship for every domain.

Reasoning allocation

Is thinking worth its additional cost?

DeepSeek V4 Flash without thinking costs about €0.0017 per exercise but falls from 97.24% to 86.31%. Thinking costs roughly 3.2 times more, yet the absolute price difference remains small.

01100 direct responses

Approximately €0.17.

02100 thinking responses

Approximately €0.56.

03Marginal purchase

About €0.39 buys 10.93 score points.

This differs sharply from the Sol comparison, where a 72-fold increase buys 1.48 points. The useful question is not whether thinking is more expensive, but how much additional accuracy each euro purchases.

Why cheaper does not always mean better value

Haiku, GPT-4.1 and Sonnet cost less than frontier models but score roughly 65–72%. DeepSeek Flash is both cheaper and substantially more accurate. A low nominal price is therefore insufficient: correction, regeneration and external verification can make an apparently inexpensive model the costlier system.

Product distinction

Subscriptions and APIs sell different things

As documented on 12 Aug 2026, ChatGPT Plus ↗ was separate from API billing and subject to product limits. Claude Pro ↗ likewise separated subscription and API access, while Google AI Pro ↗ bundled Gemini with storage and other services. Current terms should be checked on those first-party pages.

APIMeasured computationAutomation, metering and reproducible unit costs
SubscriptionIntegrated product accessInterface, files, storage, tools and persistent conversations

Their prices can be compared, but their value cannot be reduced to token costs alone.

Decision framework

The most efficient strategy may use more than one model

The benchmark does not support a universal rule that APIs are for low usage and subscriptions for high usage. The decision should instead ask how many substantial requests are made, how long conversations and files are, whether automation matters, what an incorrect answer costs, whether a 99% model is sufficient and whether plan limits fit the intended workflow.

The observed panel motivates a retrospective hypothesis: use DeepSeek V4 Flash for most requests and reserve GPT-5.6 Sol or Claude Fable 5 for ambiguous or difficult cases. This is not a validated prospective policy; it can be examined as a benchmark-based simulation in the Playground ↗.

How much is the final percentage point worth—and is the most expensive model needed for every request?

Those questions are more informative than asking which model is simply “best.”

References

Sources and further reading

Pricing note. Cost figures are historical estimates based on the rates recorded with the benchmark runs. Provider prices, peak/off-peak rules, exchange rates and subscription limits can change; current commercial pages may therefore differ from the archived snapshot.