Claude Opus 4.7 (Non-reasoning, High Effort) vs o3: The Ultimate Performance & Pricing Comparison

Claude Opus 4.7 (Non-reasoning, High Effort) leads the available intelligence comparison, while o3 is substantially cheaper and has the only reported output-speed measurement. The available evidence supports a conditional choice, not a universal winner. Claude scores 42.7 on the Artificial Analysis Intelligence Index, compared with 30.4 for o3. o3 costs $3.5 per 1M blended tokens, compared with $10 for Claude. The two models share a reported latency of 0.3 seconds, but Claude has no reported median output speed in the supplied dataset.\n\nThe central selection problem is evidence quality. The supplied materials do not establish a like-for-like coding benchmark, context-window comparison, stable API identifier, or reliable community verdict for either exact configuration. Anthropic’s model overview does not independently document the Non-reasoning, High Effort variant, while OpenAI’s model directory does not currently list o3. Data provided by https://artificialanalysis.ai/

Claude Opus 4.7 (Non-reasoning, High Effort) is the measured intelligence leader, but o3 offers the clearer economic and throughput case. The Artificial Analysis Intelligence Index places Claude at 42.7 and o3 at 30.4. That gap is meaningful for teams choosing a general-purpose model, yet it does not prove that Claude will win every coding, mathematics, or agent workflow. The supplied data includes an o3 Mathematics Index score of 88.3, but no corresponding Claude score.\n\nFor budget-sensitive production systems, o3 is the practical default. Its blended price is $3.5 per 1M tokens, versus $10 for Claude. Its input price is $2 per 1M tokens, versus $5, and its output price is $8, versus $25. Output-heavy workloads therefore face a particularly strong cost argument for o3.\n\nFor quality-first evaluation, Claude deserves the first test slot because its measured intelligence score is higher. However, the exact deployment status needs verification. Anthropic’s overview identifies Claude Opus 4.7 and documents a 300,000-token output limit for Message Batches with a beta header, but it does not establish the same limit for synchronous Messages API calls. OpenAI’s current model documentation does not confirm o3 availability, a stable alias, or an API endpoint.\n\nThe safest conclusion is simple: choose o3 for cost-controlled, speed-sensitive workloads after confirming access, and test Claude for tasks where higher general intelligence could reduce retries, supervision, or downstream correction.

Claude Opus 4.7 (Non-reasoning, High Effort) has the stronger measured general-intelligence signal, while o3 has the stronger observed throughput signal. Claude’s Artificial Analysis Intelligence Index is 42.7, compared with 30.4 for o3. That difference suggests Claude may be the better first candidate for complex instruction following, broad synthesis, and tasks where several kinds of judgment appear in one request. It does not isolate coding quality, repository navigation, tool use, or factual reliability.\n\nThe mathematics comparison is not decisive. o3 has an Artificial Analysis Mathematics Index score of 88.3, while Claude has no reported value in the supplied data. Developers should not infer that Claude is weaker at mathematics from a missing score. They should also avoid presenting o3’s 88.3 as proof that it is better for every reasoning task. The benchmark coverage is asymmetric, so a targeted evaluation remains necessary.\n\no3 is the only model with a reported median output speed, at 128.056 output tokens per second. Claude has no reported value for that metric. This makes o3 easier to assess for streaming interfaces, interactive coding assistants, and workloads where users wait for generated text. The absence of a Claude speed result is evidence of uncertainty, not evidence that Claude is slower.\n\nBoth models show a reported latency of 0.3 seconds in the supplied dataset. That tie matters because a faster token stream does not automatically mean a faster first response. Developers should separate request startup, time to first token, sustained generation, tool-call pauses, and total task completion. The supplied materials do not provide those additional measurements.\n\nAnthropic’s official documentation adds another boundary condition: Claude Opus 4.7 can use Message Batches with up to 300,000 output tokens and the output-300k-2026-03-24 beta header. The model overview does not justify transferring that limit to synchronous calls. For long-running generation, the API mode may therefore change the practical result.

o3 is the clear price leader, but Claude Opus 4.7 (Non-reasoning, High Effort) can still be economically rational if higher quality reduces repeated work. o3 costs $3.5 per 1M blended tokens, compared with $10 for Claude. The supplied blended figure uses a 3-to-1 input-to-output mix, so it is a useful planning baseline rather than a universal invoice estimate.\n\nThe price gap widens for output-heavy applications. Claude lists $5 per 1M input tokens and $25 per 1M output tokens. o3 lists $2 per 1M input tokens and $8 per 1M output tokens. A chat product that generates long explanations, code patches, or structured documents will feel the output-price difference more sharply than a workload dominated by short responses.\n\nA cheaper token is not always a cheaper completed task. If o3 requires more retries, longer prompts, additional validation calls, or human review to reach the same acceptance rate, its lower listed price may not survive an end-to-end cost calculation. The supplied materials do not report retry rates, task success rates, correction effort, or production quality. That evidence gap prevents a defensible total-cost winner.\n\nClaude’s tokenizer also changes the calculation. Anthropic’s pricing documentation says Claude 4.7 and later models use a new tokenizer, with the same text usually producing about 30% more tokens. The actual increase depends on content and workload. Teams moving an existing prompt from another model should therefore measure token counts on representative traffic before forecasting spend.\n\nCaching can alter the comparison for repeated context. Anthropic lists 5-minute cache writes at $6.25 per 1M tokens, 1-hour cache writes at $10, and cache hits and refreshes at $0.50. The supplied o3 materials do not provide comparable current pricing details, so cache-adjusted parity cannot be established from this brief.

o3 is the best first choice for teams that prioritize low token cost, measurable streaming speed, and mathematics evidence. Its $3.5 blended price and 128.056 reported median output tokens per second create a strong operating baseline. The recommendation assumes the team can confirm that o3 remains callable through its intended platform, because OpenAI’s current model directory does not list o3 or document a stable alias in the supplied material.\n\nClaude Opus 4.7 (Non-reasoning, High Effort) is the better candidate for quality-first experiments involving broad, difficult tasks. Its 42.7 Intelligence Index score exceeds o3’s 30.4. That result supports testing Claude where improved first-pass quality could reduce review time or retries. It does not establish a coding-specific advantage, because no exact-variant coding evaluation or reliable community test is provided.\n\nUse a two-stage decision process:\n\n1. Confirm model access, API identifiers, request modes, output limits, and billing behavior with the relevant provider documentation. Anthropic’s overview distinguishes Message Batches from ordinary synchronous usage, while OpenAI’s pricing documentation does not list a current o3 price in the supplied official material.\n2. Run the same representative tasks through both models, recording acceptance rate, retries, time to first token, total completion time, token counts, and human correction effort.\n\nChoose Claude if its quality advantage survives that test and offsets its higher spend. Choose o3 if the task quality is acceptable and access is stable. Do not choose based on the 88.3 mathematics score alone, because Claude has no matching mathematics result and o3’s broader product status is not confirmed by the supplied official directory.

Claude Opus 4.7 (Non-reasoning, High Effort) should enter production only after teams verify that the exact configuration is callable and its limits match the intended request path. Anthropic’s documentation names Claude Opus 4.7 but does not independently specify this variant’s API ID, context window, synchronous output limit, or multimodal behavior.\n\no3 requires the same verification from OpenAI. The current model directory does not list o3 in the supplied material, and the current pricing page does not provide a current o3 price there. The benchmark dataset still reports o3 at $3.5 per 1M blended tokens, so teams should reconcile that data snapshot with live billing before committing budget.\n\nThe evidence is strong enough to form a test order, not strong enough to skip testing. Start with o3 for cost and speed validation, then test Claude for quality-sensitive tasks where its 42.7 Intelligence Index score may matter.