DeepSeek V4 Pro to V4 Pro 0813 migration guide

August 13, 2026 · By Sharjeel Abbas

DeepSeek V4 Pro 0813 is a separate GA model ID, not a safe label swap for the earlier V4 Pro entry. Its public base prices are lower and its listed context is one million tokens, but behavioral compatibility still requires a measured migration.

The primary catalog sources for this analysis are OpenRouter's DeepSeek V4 Pro 0813 listing and OpenRouter's Grok 4.6 listing. Specifications and prices below were checked against OpenRouter's models API on August 13, 2026. Provider metadata can change, so production buyers should recheck the live listing before committing a fixed budget.

Related reading:

• Chairman model responsibilities
• Using the million-token context
• Hallucination reduction checklist

Why both IDs remain in the catalog

Saved debates are audit records. If an old assembly generated a verdict with deepseek/deepseek-v4-pro, changing its label or runtime behind the scenes would make reproduction misleading. RigorDesk therefore adds deepseek/deepseek-v4-pro-0813 as a new entry. Users can compare them directly, and historical transcripts retain the correct producer identity.

The 0813 listing identifies the release as GA and reports $0.435/M input, $0.87/M output, and a 1,048,576-token context. The older V4 Pro listing remains separate. Lower list prices may substantially reduce repeated-review cost, but a fair comparison must capture output length and retries because those can outweigh a base-rate improvement.

Compatibility tests that matter

Replay prompts that exercise tool selection, response formats, reasoning effort, long evidence, multilingual text, and edge-case instructions. Validate structured output even though response formats are supported. Compare citations against the same source packet. For chairman use, score whether minority objections remain visible and whether the verdict separates facts, inferences, and unresolved questions.

Do not use only easy prompts. Include cases where the earlier model refused, hallucinated, timed out, or produced an empty response. A GA label suggests release maturity but does not prove that every failure class improved. Promote the 0813 ID when it meets explicit thresholds, then keep the old ID for historical work and a short rollback window.

Separate metadata improvements from behavior

The 0813 listing establishes a 1,048,576-token context window, text-only input, reasoning and tool support, and low published token prices. Those facts change what workloads are economically possible, but they do not establish compatibility with prompts tuned for the earlier V4 Pro entry. A new model may interpret role instructions differently, produce longer answers, choose tools at different rates, or retrieve evidence differently across a large context. Each change must be measured rather than inferred from the GA label.

Keep the old and new IDs visible in the catalog and name them explicitly in evaluation reports. Do not update historical assembly snapshots or rewrite old cost assumptions. When a user reruns a previous case for comparison, let them select the original model or create a new versioned assembly. Reproducibility is not administrative overhead; it is the only way to distinguish a model change from a changed prompt, evidence packet, provider route, or debate protocol.

Add tests for the larger operating envelope

The migration suite should include ordinary prompts that fit both versions and a separate ladder of long-context cases. Place supported facts at several depths, add near-duplicate distractors, and include questions whose answer is absent. Require source identifiers and inspect whether cited passages entail the conclusion. Compare full-context submission with retrieval-based narrowing. The new window is valuable only if it improves supported coverage without an unacceptable increase in latency, omission, or false citation.

Test tool calls and response formats under truncation and provider errors. Validate tool arguments before execution and validate structured responses on return. Measure completion length and retry behavior because a lower per-token rate can be offset by verbose output or repeated failures. For multi-round debates, observe how transcript growth affects later prompts. A migration scorecard should describe completed review cost and success, not only the first model response.

Promote by seat and workload

DeepSeek V4 Pro 0813 may first earn the long-context analyst seat, where its listed capacity and price offer a clear hypothesis to test. It may later replace the earlier version as a challenger or chairman if paired cases support that change. Treat each seat as a different job with different failure consequences. A strong analyst can still be a weak synthesizer if it compresses dissent, and a strong chairman can still be inefficient for broad extraction.

Run a limited canary and retain the earlier assembly as a rollback target. Trigger rollback on critical missed evidence, unsupported claims, tool regressions, schema failures, provider instability, or total-cost breaches. Review failures instead of deleting them from the comparison set. Once the new version clears a representative operating window, update defaults prospectively while preserving historical IDs. This sequence captures the benefits of the GA release without turning every saved workflow into an uncontrolled experiment.

Decision table

Visual summary

Verified specification baseline

The table is a capability and cost baseline, not a quality ranking. A larger context window does not prove better retrieval from the middle of a long prompt. A lower token price does not prove lower total task cost because output length, retries, reasoning tokens, and tool calls all affect the bill. A multimodal input declaration confirms accepted media types, not accuracy on every chart, screenshot, scan, or document.

Neither listing supplied a new, independently replicated benchmark suite at publication time. That absence matters. It is reasonable to describe Grok 4.6 as intended for coding, knowledge work, and STEM because the provider says so; it is not reasonable to turn that sentence into an unqualified claim that Grok wins a particular coding or science benchmark. The same rule applies to the DeepSeek GA label: general availability describes release maturity, not guaranteed superiority over the earlier model on every workload.

How to evaluate the models on RigorDesk

Start with a controlled case set drawn from real work. Keep the source packet, prompt, output contract, reasoning setting, web-search setting, and maximum output length fixed. Randomize seat order or use a silent Delphi first round so the first model does not anchor the rest. Record model IDs rather than family names because deepseek/deepseek-v4-pro and deepseek/deepseek-v4-pro-0813 are different runtime contracts.

Score outcomes that users can inspect: factual claims supported by the attached evidence, important objections found, invalid objections avoided, instructions followed, useful citations produced, schema validity, completion latency, and metered cost. For coding work, add tests passed and regressions introduced. For document review, add page-level evidence recall and whether the model distinguishes missing evidence from negative evidence. For a debate, preserve dissent instead of rewarding superficial agreement.

Run enough cases to expose variance. A single polished response is a demonstration, not an evaluation. Compare medians and failure distributions, then read the worst failures. Expensive mistakes are often concentrated in a small class of prompts: very long inputs, malformed files, ambiguous requirements, or tasks that require several tools. Those tail cases should influence the final seat assignment more than a small difference in average style scores.

Deployment checklist

• Create a new assembly instead of editing historical model identity.
• Compare actual provider cost, not only the headline rate.
• Test chairman dissent preservation and schema validity.
• Retain the earlier V4 Pro ID for replay and rollback.

On RigorDesk, both models are in the paid catalog and can be selected in assemblies, debates, Draft, and Review. Paid plans share access to the complete model catalog; Pro Max changes compute allowance and round depth. Prepaid credits also unlock paid models in the web app. The editor estimates a run before launch, while the audit trail records actual token use and provider cost after completion.

Model availability is only one layer of a reliable workflow. Keep evidence attached, define role boundaries, require explicit uncertainty, and assign a separate chairman or synthesizer when the decision is consequential. The goal is not to prove that one vendor always wins. The goal is to discover which model contributes the most independent, verifiable value for a specific class of decisions.