CoGrader vs New API
Side-by-side comparison · Updated October 2026
| Description | CoGrader is a teacher-facing AI grading assistant for essays and other open-ended assignments. It uses a selected or custom rubric to draft grades and feedback that educators can review and edit before returning work. Its useful role is helping a teacher organize assessment and feedback; it does not establish that a grade is correct, unbiased or suitable for a particular student without human review. The free Starter plan includes 100 student submissions per month and rubric creation and sharing. The pricing page also advertises 90 days of premium access, which is a temporary benefit rather than unlimited free access to paid features. Standard includes 350 submissions per month, handwritten assignments, grammar checking and a class-performance dashboard. It costs $19 per month on monthly billing or an advertised $15 per month billed annually. The annual equivalent is $180 before any applicable additions, calculated as $15 multiplied by 12; confirm the actual checkout total before paying. Schools and Districts plans use a custom quote and advertise unlimited submissions, shared rubric libraries, administration, institutional analytics and training. Higher Ed and Enterprise also use a custom quote, with API access, custom LMS connections and roles among the listed options. Choose a plan around submission volume, the review process and the integrations your institution actually needs, rather than assuming an individual subscription includes enterprise access. To evaluate CoGrader, begin with a rubric that defines each criterion and the evidence needed for each score. Try a small, permitted sample of work you have already assessed, compare the suggested results with your own reasoning, and revise unclear rubric language. Check whether each comment refers accurately to the student's work and gives an actionable next step. Review accommodations, language-learning needs and subject-specific expectations before finalizing feedback. A class dashboard can help identify topics to revisit; it should not replace the teacher's judgment about individual learning needs. Google Classroom integration is described as available to all users. The pricing FAQ places full Canvas and Schoology integration in school or district subscriptions, although the plan cards also display those platforms elsewhere. Confirm the exact integration and account entitlement you need. Other LMS workflows may use file import and export. The vendor also advertises plagiarism and AI-writing detection, but its plan card and FAQ disagree about AI-detection access. Confirm the selected plan's access, and treat a flag as a reason to review the evidence rather than proof of misconduct. CoGrader's privacy policy says teachers provide assignment questions, rubrics and student answers, and that student grading data is not used to train its AI models. It says third-party AI providers may not train on that data and identifies OpenAI OpCo, LLC as a provider receiving anonymized grading information. The policy also allows anonymized aggregate information to improve the service and does not give one fixed deletion deadline. Follow your school's authorization and data-handling process before uploading student work; a vendor policy is a statement of practice, not an independent security assessment. CoGrader is most relevant when an educator needs rubric-based feedback at a recurring classroom workload. Compare EssayGrader using the same sample rubric, feedback-review steps, submission allowance and data requirements. The terms describe a refund window within 14 days of an initial subscription purchase; that is separate from the free plan's advertised premium-access period. Review billing and cancellation terms before subscribing. | New API is a self-hosted AI gateway and model-management project maintained in the QuantumNous repository. It brings provider channels, access tokens, model restrictions, usage statistics and cost accounting into one interface. Teams supply their own authorized model-provider access and operate the gateway in their chosen environment. The gateway supports several API formats, including OpenAI-compatible requests, Claude Messages and Google Gemini. Compatibility has boundaries: the README marks Gemini-to-OpenAI conversion as text-only without function calling, and OpenAI-compatible to Responses conversion as in development. Test the exact endpoints, streaming behavior and tool calls your application uses before switching traffic. Routing features include weighted channel selection, automatic retry after failures and user-level model rate limits. The dashboard supports request-based, usage-based and cache-hit cost accounting, with token grouping and model-access controls. These controls can help organize usage, but retries and a common API format do not guarantee uninterrupted service or identical behavior across providers. The current repository license is AGPLv3. Docker Compose is the recommended quick-start path in the README, which also documents Docker commands with SQLite or MySQL. Running the software still involves infrastructure, operations and upstream model charges. Review the current license, secure your deployment and validate accounting against provider bills. Compare LiteLLM if you also want a Python SDK or a documented gateway for MCP servers and agents. |
| Category | Education | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Freemium | Open Source |
| Starting Price | Free | N/A |
| Plans |
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| Use Cases |
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| Tags | AI essay gradingrubric feedbackteacher assessmentGoogle Classroomeducation | AI gatewayLLM routingmodel managementrate limitingusage accounting |
| Features | ||
| Rubric-based AI grades and feedback for teacher review | ||
| Free Starter: 100 student submissions per month | ||
| Standard: 350 submissions per month | ||
| Custom and standards-aligned rubrics | ||
| Handwritten assignments and grammar checking on Standard | ||
| Google Classroom integration and institutional LMS options | ||
| Class-performance dashboard and institutional analytics | ||
| Quoted API access for Higher Ed and Enterprise | ||
| Self-hosted AI gateway and model management | ||
| Provider channels, token groups and model restrictions | ||
| OpenAI-compatible, Claude Messages and Gemini format support | ||
| Documented limits on protocol conversion | ||
| Weighted channel selection and failure retries | ||
| User-level model rate limiting | ||
| Request, usage and cache-hit cost accounting | ||
| Docker Compose deployment documentation | ||
| View CoGrader | View New API | |
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